In [1]:
  # python active_clustering.py --dataset iris --num_clusters 3 --num_seeds 10
# python active_clustering.py --dataset 20_newsgroups_all --feature_extractor TFIDF --max-feedback-given 100 --num_clusters 20 --verbose
# python active_clustering.py --dataset 20_newsgroups_sim3 --feature_extractor TFIDF --max-feedback-given 500 --num_clusters 3 --verbose
# python active_clustering.py --dataset 20_newsgroups_diff3 --feature_extractor TFIDF --max-feedback-given 500 --num_clusters 3 --verbose

'''
python active_clustering.py --dataset synthetic_data \
    --num_clusters 5 \
    --num-seeds 5 \
    --plot-clusters \
    --plot-dir /tmp/synthetic_data_vanilla_kmeans_clusters

python active_clustering.py --dataset OPIEC59k --data-path \
    /projects/ogma1/vijayv/okb-canonicalization/clustering/data \
    --dataset-split test \
    --num_clusters 490 \
    --num_seeds 5

python active_clustering.py --dataset OPIEC59k \
    --data-path /projects/ogma1/vijayv/okb-canonicalization/clustering/data \
    --dataset-split test \
    --num_clusters 490 \
    --num_seeds 1 \
    --normalize-vectors \
    --init k-means++ \
    --verbose |& tee ~/logs/canon/opiec_clustering_simplified_kmeanspp.log
'''

from sklearn import metrics
from sklearn.cluster import AgglomerativeClustering
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.preprocessing import normalize
import jsonlines


import argparse
from collections import defaultdict
import json
import matplotlib.pyplot as plt
import numpy as np
import os
import pickle
import random
import sys
import time
import torch


import sys
#sys.path.append("cmvc")

from dataloaders import load_dataset, generate_synthetic_data
from experiment_utils import set_seed, summarize_results


from active_semi_supervised_clustering.active_semi_clustering.semi_supervised.pairwise_constraints import PCKMeans, CardinalityConstrainedPCKMeans,GPTExpansionClustering, KMeansCorrection
from active_semi_supervised_clustering.active_semi_clustering.semi_supervised.labeled_data.kmeans import KMeans
# from sklearn.cluster import KMeans
from active_semi_supervised_clustering.active_semi_clustering.semi_supervised.labeled_data.seededkmeans import SeededKMeans
from active_semi_supervised_clustering.active_semi_clustering.semi_supervised.labeled_data.constrainedkmeans import ConstrainedKMeans
from active_semi_supervised_clustering.active_semi_clustering.active.pairwise_constraints import construct_pairwise_oracle_single_example, GPT3ComparativeOracle, DistanceBasedSelector, LabelBasedSelector, ExploreConsolidate, MinMax, SimilarityFinder, MinMaxFinetune
from active_semi_supervised_clustering.active_semi_clustering.active.pairwise_constraints import Random

from cmvc.helper import invertDic
from cmvc.metrics import pairwiseMetric, calcF1
from cmvc.test_performance import cluster_test
from cmvc.model_max_margin import KGEModel
from cmvc.Context_view import BertClassificationModel

from eval_utils import cluster_acc

Initialisation du parser¶

In [2]:
parser = argparse.ArgumentParser()
parser.add_argument('--dataset', type=str, choices=["iris", "tweet", "clinc", "bank77", "20_newsgroups_all", "20_newsgroups_full", "20_newsgroups_sim3", "20_newsgroups_diff3", "reverb45k", "OPIEC59k", "reverb45k-raw", "OPIEC59k-raw", "OPIEC59k-kg", "OPIEC59k-text", "synthetic_data"], default="iris", help="Clustering dataset to experiment with")
parser.add_argument("--algorithms", action="append")
parser.add_argument('--data-path', type=str, default=None, help="Path to clustering data, if necessary")
parser.add_argument('--dataset-split', type=str, default=None, help="Dataset split to use, if applicable")
parser.add_argument('--num_clusters', type=int, default=3)
parser.add_argument('--pckmeans-w', type=float, default=0.25, help="The 'w' parameter for pairwise constraint k-means")
parser.add_argument('--max-feedback-given', type=int, default=100, help="Number of instances of user feedback (e.g. oracle queries) allowed")
parser.add_argument('--num-corrections', type=int, default=None)
parser.add_argument('--num_seeds', type=int, default=10)
parser.add_argument('--num-reinit', type=int, default=1)
parser.add_argument('--feature_extractor', type=str, choices=["identity", "BERT", "TFIDF"], default="identity")
parser.add_argument('--normalize-vectors', action="store_true", help="Normalize vectors")
parser.add_argument('--split-normalization', action="store_true", help="Normalize per-view components separately (for multi-view clustering)")
parser.add_argument('--init', type=str, choices=["random", "k-means++", "k-means"], default="random", help="Initialization algorithm to use for k-means.")
parser.add_argument('--plot-clusters', action="store_true", help="Whether to plot clusters")
parser.add_argument('--plot-dir', type=str, default=None, help="Directory to store cluster plots")
parser.add_argument('--verbose', action="store_true")
Out[2]:
_StoreTrueAction(option_strings=['--verbose'], dest='verbose', nargs=0, const=True, default=False, type=None, choices=None, required=False, help=None, metavar=None)

Définition des fonctions¶

In [3]:
def sample_cluster_seeds(features, labels, max_feedback_given = 0, aggregate="mean"):
    assert len(features) == len(labels)
    labels_list = [-1 for _ in range(len(features))]

    original_index_by_cluster = defaultdict(list)
    for i, (f, l) in enumerate(zip(features, labels)):
        original_index_by_cluster[l].append(i)

    label_values = list(original_index_by_cluster.keys())
    random.shuffle(label_values)

    min_feedback_per_label = max_feedback_given // len(label_values)
    num_labels_with_extra_point = max_feedback_given % len(label_values)
    feedback_per_label = [min_feedback_per_label + int(i < num_labels_with_extra_point) for i in range(len(label_values))]


    feedback_counter = 0
    for i, label in enumerate(label_values):
        num_feedback_for_label = min(len(original_index_by_cluster[label]), feedback_per_label[i])
        labeled_point_indices = random.sample(original_index_by_cluster[label], num_feedback_for_label)
        for point_index in original_index_by_cluster[label]:
            if point_index in labeled_point_indices:
                labels_list[point_index] = label
                feedback_counter += 1

    assert feedback_counter <= max_feedback_given

    return np.array(labels_list)
In [4]:
def construct_pairwise_oracle_prompt(dataset_name, documents, side_information):
    if isinstance(side_information, list):
        side_info = None
    else:
        side_info = side_information.side_info
    if dataset_name == "OPIEC59k":
        instruction = """You are tasked with clustering entity strings based on whether they refer to the same Wikipedia article. To do this, you will be given pairs of entity names and asked if their anchor text, if used separately to link to a Wikipedia article, is likely referring to the same article. Entity names may be truncated, abbreviated, or ambiguous.

To help you make this determination, you will be given up to three context sentences from Wikipedia where the entity is used as anchor text for a hyperlink. Amongst each set of examples for a given entity, the entity for all three sentences is a link to the same article on Wikipedia. Based on these examples, you will decide whether the first entity and the second entity listed would likely link to the same Wikipedia article if used as separate anchor text.

Please note that the context sentences may not be representative of the entity's typical usage, but should aid in resolving the ambiguity of entities that have similar or overlapping meanings.

To avoid subjective decisions, the decision should be based on a strict set of criteria, such as whether the entities will generally be used in the same contexts, whether the context sentences mention the same topic, and whether the entities have the same domain and scope of meaning.

Your task will be considered successful if the entities are clustered into groups that consistently refer to the same Wikipedia articles."""
        example_1 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["B.A"]], documents[side_info.ent2id["M.D."]], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_2 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["B.A"]], documents[side_info.ent2id["bachelor"]], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_3 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["Duke of York"]], documents[side_info.ent2id["Frederick"]], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_4 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["Academy Award"]], documents[side_info.ent2id["Best Actor in Supporting Role"]], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        prefix = "\n\n".join([example_1, example_2, example_3, example_4])
    elif dataset_name == "reverb45k":
        instruction = """You are tasked with clustering entity strings based on whether they link to the same entity on the Freebase knowledge graph. To do this, you will be given pairs of entity names and asked if these strings, if linked to a knowledge graph, are likely referring to the same entity (e.g. a concept, person, or organization). Entity names may be truncated, abbreviated, or ambiguous.

To help you make this determination, you will be given up to three context sentences from the internet that mention an entity. Amongst each set of examples for a given entity, assume that the entity mentioned in all three context sentences links refers to the same object. Based on these examples, you will decide whether the first entity and the second entity listed are likely to link to the *same* knowledge graph entity.

Please note that the context sentences may not be representative of the entity's typical usage, but should aid in resolving the ambiguity of entities that have similar or overlapping meanings.

To avoid subjective decisions, the decision should be based on a strict set of criteria, such as whether the entities will generally be used in the same contexts, whether the entities likely refer to the same person or organization, whether the context sentences mention the same topic, and whether the entities have the same domain and scope of meaning.

Your task will be considered successful if the entities are clustered into groups that consistently link to the same knowledge graph node."""
        example_1 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["Hannibal"]], documents[side_info.ent2id["Hannibal Barca"]], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_2 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["Lutheran Church"]], documents[side_info.ent2id["Church"]], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_3 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["Grove Art Online"]], documents[side_info.ent2id["Oxford Art Online"]], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_4 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["Charlie Williams"]], documents[side_info.ent2id["Williams"]], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        prefix = "\n\n".join([example_1, example_2, example_3, example_4])
    elif dataset_name == "tweet":
        instruction = """You are tasked with clustering tweets based on whether they discuss the same topic. To do this, you will be given pairs of (stopword-removed) tweets and asked if they discuss the same topic. To avoid subjective decisions, the decision should be based on a strict set of criteria, such as whether the tweets explicitly mention the same topic or whether they reflect the same contexts.

Your task will be considered successful if the tweets are clustered into groups that consistently discuss the same topic."""
        example_1 = construct_pairwise_oracle_single_example(documents[0], documents[563], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_2 = construct_pairwise_oracle_single_example(documents[4], documents[187], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_3 = construct_pairwise_oracle_single_example(documents[2135], documents[1218], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_4 = construct_pairwise_oracle_single_example(documents[2471], documents[1218], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        prefix = "\n\n".join([example_1, example_2, example_3, example_4])
    elif dataset_name == "clinc":
        instruction = """You are tasked with clustering queries for a task-oriented dialog system based on whether they express the same general user intent. To do this, you will be given pairs of user queries and asked if they express the same general user need or intent.

Your task will be considered successful if the queries are clustered into groups that consistently express the same general intent."""
        example_1 = construct_pairwise_oracle_single_example(documents[1], documents[2], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_2 = construct_pairwise_oracle_single_example(documents[70], documents[700], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_3 = construct_pairwise_oracle_single_example(documents[1525], documents[1527], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_4 = construct_pairwise_oracle_single_example(documents[1500], documents[1000], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        prefix = "\n\n".join([example_1, example_2, example_3, example_4])
    elif dataset_name == "bank77":
        instruction = """You are tasked with clustering queries for a online banking system based on whether they express the same general user intent. To do this, you will be given pairs of user queries and asked if they express the same general user need or intent.

Your task will be considered successful if the queries are clustered into groups that consistently express the same general intent."""
        example_1 = construct_pairwise_oracle_single_example(documents[0], documents[1], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_2 = construct_pairwise_oracle_single_example(documents[1990], documents[2001], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_3 = construct_pairwise_oracle_single_example(documents[2010], documents[2001], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_4 = construct_pairwise_oracle_single_example(documents[2900], documents[3000], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        prefix = "\n\n".join([example_1, example_2, example_3, example_4])
    else:
        raise NotImplementedError
    return "\n\n".join([instruction, prefix])

def construct_keyphrase_expansion_prompt(dataset_name, documents, side_information):
    if isinstance(side_information, list):
        side_info = None
    else:
        side_info = side_information.side_info
    if dataset_name == "OPIEC59k":
        instruction = """You are tasked with clustering entity strings based on whether they refer to the same Wikipedia article. To do this, you will be given pairs of entity names and asked if their anchor text, if used separately to link to a Wikipedia article, is likely referring to the same article. Entity names may be truncated, abbreviated, or ambiguous.

To help you make this determination, you will be given up to three context sentences from Wikipedia where the entity is used as anchor text for a hyperlink. Amongst each set of examples for a given entity, the entity for all three sentences is a link to the same article on Wikipedia. Based on these examples, you will decide whether the first entity and the second entity listed would likely link to the same Wikipedia article if used as separate anchor text.

Please note that the context sentences may not be representative of the entity's typical usage, but should aid in resolving the ambiguity of entities that have similar or overlapping meanings.

To avoid subjective decisions, the decision should be based on a strict set of criteria, such as whether the entities will generally be used in the same contexts, whether the context sentences mention the same topic, and whether the entities have the same domain and scope of meaning.

Your task will be considered successful if the entities are clustered into groups that consistently refer to the same Wikipedia articles."""
        example_1 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["B.A"]], documents[side_info.ent2id["M.D."]], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_2 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["B.A"]], documents[side_info.ent2id["bachelor"]], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_3 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["Duke of York"]], documents[side_info.ent2id["Frederick"]], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_4 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["Academy Award"]], documents[side_info.ent2id["Best Actor in Supporting Role"]], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        prefix = "\n\n".join([example_1, example_2, example_3, example_4])
    elif dataset_name == "reverb45k":
        instruction = """You are tasked with clustering entity strings based on whether they link to the same entity on the Freebase knowledge graph. To do this, you will be given pairs of entity names and asked if these strings, if linked to a knowledge graph, are likely referring to the same entity (e.g. a concept, person, or organization). Entity names may be truncated, abbreviated, or ambiguous.

To help you make this determination, you will be given up to three context sentences from the internet that mention an entity. Amongst each set of examples for a given entity, assume that the entity mentioned in all three context sentences links refers to the same object. Based on these examples, you will decide whether the first entity and the second entity listed are likely to link to the *same* knowledge graph entity.

Please note that the context sentences may not be representative of the entity's typical usage, but should aid in resolving the ambiguity of entities that have similar or overlapping meanings.

To avoid subjective decisions, the decision should be based on a strict set of criteria, such as whether the entities will generally be used in the same contexts, whether the entities likely refer to the same person or organization, whether the context sentences mention the same topic, and whether the entities have the same domain and scope of meaning.

Your task will be considered successful if the entities are clustered into groups that consistently link to the same knowledge graph node."""
        example_1 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["Hannibal"]], documents[side_info.ent2id["Hannibal Barca"]], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_2 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["Lutheran Church"]], documents[side_info.ent2id["Church"]], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_3 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["Grove Art Online"]], documents[side_info.ent2id["Oxford Art Online"]], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_4 = construct_pairwise_oracle_single_example(documents[side_info.ent2id["Charlie Williams"]], documents[side_info.ent2id["Williams"]], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        prefix = "\n\n".join([example_1, example_2, example_3, example_4])
    elif dataset_name == "tweet":
        instruction = """You are tasked with clustering tweets based on whether they discuss the same topic. To do this, you will be given pairs of (stopword-removed) tweets and asked if they discuss the same topic. To avoid subjective decisions, the decision should be based on a strict set of criteria, such as whether the tweets explicitly mention the same topic or whether they reflect the same contexts.

Your task will be considered successful if the tweets are clustered into groups that consistently discuss the same topic."""
        example_1 = construct_pairwise_oracle_single_example(documents[0], documents[563], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_2 = construct_pairwise_oracle_single_example(documents[4], documents[187], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_3 = construct_pairwise_oracle_single_example(documents[2135], documents[1218], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_4 = construct_pairwise_oracle_single_example(documents[2471], documents[1218], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        prefix = "\n\n".join([example_1, example_2, example_3, example_4])
    elif dataset_name == "clinc":
        instruction = """You are tasked with clustering queries for a task-oriented dialog system based on whether they express the same general user intent. To do this, you will be given pairs of user queries and asked if they express the same general user need or intent.

Your task will be considered successful if the queries are clustered into groups that consistently express the same general intent."""
        example_1 = construct_pairwise_oracle_single_example(documents[1], documents[2], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_2 = construct_pairwise_oracle_single_example(documents[70], documents[700], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_3 = construct_pairwise_oracle_single_example(documents[1525], documents[1527], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_4 = construct_pairwise_oracle_single_example(documents[1500], documents[1000], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        prefix = "\n\n".join([example_1, example_2, example_3, example_4])
    elif dataset_name == "bank77":
        instruction = """You are tasked with clustering queries for a online banking system based on whether they express the same general user intent. To do this, you will be given pairs of user queries and asked if they express the same general user need or intent.

Your task will be considered successful if the queries are clustered into groups that consistently express the same general intent."""
        example_1 = construct_pairwise_oracle_single_example(documents[0], documents[1], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_2 = construct_pairwise_oracle_single_example(documents[1990], documents[2001], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_3 = construct_pairwise_oracle_single_example(documents[2010], documents[2001], "Yes", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        example_4 = construct_pairwise_oracle_single_example(documents[2900], documents[3000], "No", dataset_name, prompt_suffix = None, text_type = None, add_label=True)
        prefix = "\n\n".join([example_1, example_2, example_3, example_4])
    else:
        raise NotImplementedError
    return "\n\n".join([instruction, prefix])

Algos de clustering¶

In [5]:
def cluster(semisupervised_algo, features, documents, labels, num_clusters, dataset_name, text_type=None, prompt_suffix=None, num_corrections=None, split=None, init="random", max_feedback_given=None, normalize_vectors=False, split_normalization=False, num_reinit=1, verbose=False, side_information=None, process_raw_data=False, pckmeans_w=None, seed=None):
    pairwise_constraint_cache_name = f"/home/gildon/Desktop/Paris_Descartes/TER/gpt4_cache/{dataset_name}_pairwise_constraint_cache.jsonl"
    sentence_unprocessing_mapping_file = f"/home/gildon/Desktop/Paris_Descartes/TER/gpt4_cache/{dataset_name}_{split}_sentence_unprocessing_map.json"
    assert semisupervised_algo in ["KMeans", "AgglomerativeClustering", "KMeansCorrection", "GPTExpansionClustering", "GPTExpansionAgglomerativeClustering", "GPTPairwiseClustering", "GPTPairwiseClusteringMinMax", "GPTPairwiseClusteringExploreSimilar", "GPTPairwiseClusteringOracleFree", "GPT_SCCL_OracleFree", "DEC", "GPT_CC_PCKMeans", "CardinalityConstrainedPCKMeans", "PCKMeans", "OraclePCKMeans", "ActivePCKMeans", "ActiveFinetunedPCKMeans", "ConstrainedKMeans", "SeededKMeans"]
    if semisupervised_algo == "KMeans":
        clusterer = KMeans(n_clusters=num_clusters, normalize_vectors=normalize_vectors, split_normalization=split_normalization, init=init, num_reinit=num_reinit, verbose=verbose)
        clusterer.fit(features)
    elif semisupervised_algo == "AgglomerativeClustering":
        clusterer = AgglomerativeClustering(n_clusters=num_clusters, linkage="complete")
        clusterer.fit(features)
    elif semisupervised_algo == "KMeansCorrection":
        labels_cache_file = f"/projects/ogma2/users/vijayv/extra_storage/okb-canonicalization/clustering/output/{dataset_name}_kmeans_labels.json"
        cluster_centers_cache_file = f"/projects/ogma2/users/vijayv/extra_storage/okb-canonicalization/clustering/output/{dataset_name}_kmeans_cluster_centers.npy"
        if os.path.exists(labels_cache_file):
            cluster_predictions = json.load(open(labels_cache_file))
            cluster_centers = np.load(cluster_centers_cache_file)
        else:
            kmeans_clusterer = KMeans(n_clusters=num_clusters, normalize_vectors=normalize_vectors, split_normalization=split_normalization, init=init, num_reinit=num_reinit, verbose=verbose)
            kmeans_clusterer.fit(features)
            cluster_predictions = kmeans_clusterer.labels_
            cluster_centers = kmeans_clusterer.cluster_centers_
            json.dump([int(l) for l in cluster_predictions], open(labels_cache_file, 'w'))
            np.save(cluster_centers_cache_file, cluster_centers)

        prompt = construct_pairwise_oracle_prompt(dataset_name, documents, side_information)
        oracle = GPT3Oracle(features, prompt, documents, dataset_name=dataset_name, prompt_suffix=prompt_suffix, text_type=text_type, max_queries_cnt=max_feedback_given, cache_file = f"/home/gildon/Desktop/Paris_Descartes/TER/gpt3_cache/{dataset_name}_pairwise_constraint_cache.jsonl")
        clusterer = KMeansCorrection(oracle, cluster_predictions, cluster_centers, labels)
        clusterer.fit(features, num_corrections = num_corrections)

    elif semisupervised_algo == "GPTExpansionClustering":
        cache_file_name = f"/home/gildon/Desktop/Paris_Descartes/TER/gpt4_cache/{dataset_name}_gpt_paraphrase_cache.jsonl"
        clusterer = GPTExpansionClustering(features, documents, algorithm="KMeans", dataset_name=dataset_name, split=split, n_clusters=num_clusters, side_information=side_information, cache_file_name=cache_file_name,model = "gpt_3.5")
        #clusterer.fit(features, labels)
        clusterer.fit(features)
        

    elif semisupervised_algo == "GPTPairwiseClusteringOracleFree":
        prompt = construct_pairwise_oracle_prompt(dataset_name, documents, side_information)
        oracle = GPT3Oracle(features, prompt, documents, dataset_name=dataset_name, prompt_suffix=prompt_suffix, text_type=text_type, max_queries_cnt=20000, cache_file = f"/home/gildon/Desktop/Paris_Descartes/TER/gpt3_cache/{dataset_name}_pairwise_constraint_cache_reprod.jsonl")
        
        
        print("Collecting Constraints")
        active_learner = DistanceBasedSelector(n_clusters=num_clusters)
        active_learner.fit(features, oracle=oracle)
        pairwise_constraints = active_learner.pairwise_constraints_

        print("Training PCKMeans")
        clusterer = PCKMeans(n_clusters=num_clusters, init=init, normalize_vectors=True, split_normalization=True, side_information=side_information, w=pckmeans_w)
        clusterer.fit(features, ml=pairwise_constraints[0], cl=pairwise_constraints[1])
        clusterer.constraints_ = pairwise_constraints
        if isinstance(oracle, GPT3Oracle) and os.path.exists(oracle.cache_file):
            oracle.cache_writer.close()
            

    else:
        raise ValueError(f"Algorithm {semisupervised_algo} not supported.")
    return clusterer
In [6]:
def generate_cluster_dicts(cluster_label_list):
    clust2ele = {}
    for i, cluster_label in enumerate(cluster_label_list):
        if cluster_label not in clust2ele:
            clust2ele[cluster_label] = set()
        clust2ele[cluster_label].add(i)

    ele2clust = invertDic(clust2ele, 'm2os')
    return ele2clust, clust2ele
In [7]:
def plot_cluster(features, gt_labels, clusterer_labels, metrics, plot_path, pairwise_constraints=None):
    fig = plt.figure()
    ax = fig.add_subplot(111)

    colors = ["#e41a1c", "#377eb8", "#4daf4a", "#984ea3", "#ff7f00"]
    colormap = dict(zip(list(set(clusterer_labels)), colors))    

    circles = []
    min_x = 0
    max_x = 0
    min_y = 0
    max_y = 0
    for feat, gt, cluster in zip(features, gt_labels, clusterer_labels):
        x, y = feat
        min_x = min(min_x, x)
        max_x = max(max_x, x)
        min_y = min(min_y, y)
        max_y = max(max_y, y)
        circles.append(plt.Circle((x, y), radius=0.5, color=colormap[cluster], alpha=0.1))
        ax.add_patch(circles[-1])
        ax.text(x, y, str(gt), horizontalalignment='center', verticalalignment='center')

    if pairwise_constraints is not None:
        must_links, cannot_links = pairwise_constraints
        for pml in must_links:
            start_x_ml, start_y_ml = features[pml[0]]
            end_x_ml, end_y_ml = features[pml[1]]
            plt.plot(np.array([start_x_ml, end_x_ml]), np.array([start_y_ml, end_y_ml]), '-', linewidth=1, color="black")
        for pcl in cannot_links:
            start_x_cl, start_y_cl = features[pcl[0]]
            end_x_cl, end_y_cl = features[pcl[1]]
            plt.plot(np.array([start_x_cl, end_x_cl]), np.array([start_y_cl, end_y_cl]), '--', linewidth=1, color="purple")

    ax.set_xlim((min_x-0.5, max_x+0.5))
    ax.set_ylim((min_y-0.5, max_y+0.5))
    nmi = metrics["nmi"]
    rand = metrics["rand_score"]
    ax.set_title(f"Comparing ground truth clusters with true labels\nNMI: {round(nmi, 3)}, Rand: {round(rand, 3)}")
    plt.legend()
    fig.savefig(plot_path)
    print(f"Saved plot to {plot_path}")
In [8]:
def compare_algorithms(features,
                       documents,
                       labels,
                       side_information,
                       num_clusters,
                       dataset_name,
                       num_corrections=None,
                       split=None,
                       max_feedback_given=None,
                       num_reinit=1,
                       algorithms=["KMeans", "PCKMeans", "ConstrainedKMeans", "SeededKMeans"],
                       num_seeds=3,
                       verbose=True,
                       normalize_vectors=False,
                       split_normalization=False,
                       init="random",
                       plot_clusters=False,
                       cluster_plot_dir_prefix=None,
                       dataset=None,
                       process_raw_data=False,
                       pckmeans_w=None):
    algo_results = defaultdict(list)
    timer = time.perf_counter()

    if normalize_vectors:
        if verbose:
            print(f"Starting feature normalization.")
        if split_normalization:
            timer = time.perf_counter()
            kg_features = normalize(features[:, :300], axis=1, norm="l2")
            bert_features = normalize(features[:, 300:], axis=1, norm="l2")
            features = np.hstack([kg_features, bert_features])
        else:
            features = normalize(features, axis=1, norm="l2")
        if verbose:
            print(f"Feature normalization took {round(time.perf_counter() - timer, 3)} seconds.")

    if verbose:
        print(f"Starting comparison of {num_seeds} seeds:")


    for i, seed in enumerate(range(num_seeds)):

        '''
        if dataset == "synthetic_data":
            features, labels = generate_synthetic_data(n_samples_per_cluster=200, global_seed=seed)
            assert set(y) == set(range(len(set(y))))
        '''

        if verbose:
            print(f"Starting experiments for {i}th seed")
        set_seed(seed)
        for semisupervised_algo in algorithms:
            if verbose:
                print(f"Running {semisupervised_algo} for seed {seed}")
            start_time = time.perf_counter()
            clusterer = cluster(semisupervised_algo, features, documents, labels, num_clusters, dataset_name, num_corrections=num_corrections, split=split, max_feedback_given=max_feedback_given, normalize_vectors=normalize_vectors, split_normalization=split_normalization, init=init, num_reinit=num_reinit, verbose=verbose, side_information=side_information, process_raw_data=process_raw_data, pckmeans_w=pckmeans_w, seed=seed)
            elapsed_time = time.perf_counter() - start_time
            if verbose:
                print(f"Took {round(elapsed_time, 3)} seconds to cluster points.")
            
            # np.save(open("/projects/ogma1/vijayv/okb-canonicalization/clustering/output/OPIEC59k_test_1/OPIEC59k_clusters/kmeans/cluster_centers.npy", 'wb'), clusterer.cluster_centers_)
            # 
            # breakpoint()
            metric_dict = {}
            algo_results[semisupervised_algo].append(metric_dict)
            if dataset_name.split('-')[0] == "OPIEC59k" or dataset_name.split('-')[0] == "reverb45k":
                optimal_results = cluster_test(side_information.p, side_information.side_info, labels, side_information.true_ent2clust, side_information.true_clust2ent)
                _, _, _, _, _, _, _, _, _, optimal_macro_f1, optimal_micro_f1, optimal_pairwise_f1, _, _, _, _ \
                    = optimal_results
                ave_prec, ave_recall, ave_f1, macro_prec, micro_prec, pair_prec, macro_recall, micro_recall, pair_recall, macro_f1, micro_f1, pairwise_f1, model_clusters, model_Singletons, gold_clusters, gold_Singletons  = cluster_test(side_information.p, side_information.side_info, clusterer.labels_, side_information.true_ent2clust, side_information.true_clust2ent)

                # Compute Macro/Macro/Pairwise F1 on OPIEC59k
                metric_dict["macro_f1"] = macro_f1
                metric_dict["micro_f1"] = micro_f1
                metric_dict["pairwise_f1"] = pairwise_f1
                print(f"metric_dict: {metric_dict}")

            rand_score = metrics.adjusted_rand_score(labels, clusterer.labels_)
            metric_dict["rand"] = rand_score
            nmi = metrics.normalized_mutual_info_score(labels, clusterer.labels_)
            metric_dict["nmi"] = nmi

            acc = cluster_acc(np.array(clusterer.labels_), np.array(labels))
            metric_dict["acc"] = acc

            _, pred_clust2ele = generate_cluster_dicts(clusterer.labels_)
            gt_ele2clust, gt_clust2ent = generate_cluster_dicts(labels)
            pair_prec, pair_recall = pairwiseMetric(pred_clust2ele, gt_ele2clust, gt_clust2ent)
            metric_dict["general_pairwise_f1"] = calcF1(pair_prec, pair_recall)

            if plot_clusters:
                cluster_plot_dir = cluster_plot_dir_prefix + "_".join(semisupervised_algo.split())
                os.makedirs(cluster_plot_dir, exist_ok=True)

                clustering_plot_path = os.path.join(cluster_plot_dir, f"{seed}.jpg")
                pcs = None if not hasattr(clusterer, "constraints_") else clusterer.constraints_
                plot_cluster(features, labels, clusterer.labels_, {"rand_score": rand_score, "nmi": nmi}, clustering_plot_path, pairwise_constraints=pcs)

        if verbose:
            print("\n")
    return algo_results
In [9]:
def extract_features(dataset, feature_extractor, verbose=False):
    assert feature_extractor in ["identity", "BERT", "TFIDF"]
    if feature_extractor == "identity":
        return dataset
    elif feature_extractor == "TFIDF":
        vectorizer = TfidfVectorizer(max_features=100000, min_df=5, encoding='latin-1', stop_words='english', lowercase=True)
        matrix = np.array(vectorizer.fit_transform(dataset).todense())
        if verbose:
            print(f"Dataset dimensions: {matrix.shape}")
        return matrix
    elif feature_extractor == "BERT":
        raise NotImplementedError
In [ ]:
 
In [ ]:
 
In [ ]:
 
In [ ]:
 
In [ ]:
 
In [ ]:
 
In [10]:
sys.argv =['active_clustering.py', '--dataset', 'bank77', '--data-path', 'Desktop/Paris_Descartes/TER/Recherche_datasets/Bank77/train.csv', '--feature_extractor', 'identity', '--num_clusters', '77', '--verbose']

import sys

if __name__ == "__main__":
    
    args = parser.parse_args()
    algorithms=args.algorithms
In [11]:
    X, y, documents, side_information = load_dataset(args.dataset, args.data_path, args.dataset_split, use_dse_encoder=False)
    print(X)
    
    #assert set(y) == set(range(len(set(y)))), breakpoint()
    features = extract_features(X, args.feature_extractor, args.verbose)
Found cached dataset parquet (/home/gildon/.cache/huggingface/datasets/parquet/banking77-c7022a8f2e2f5178/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec)
  0%|          | 0/2 [00:00<?, ?it/s]
load INSTRUCTOR_Transformer
max_seq_length  512
[[-0.03783553  0.00848664  0.00019302 ... -0.0047829   0.02588966
   0.02524289]
 [-0.02376927  0.01276117 -0.01331362 ... -0.0004264   0.00624872
   0.06620735]
 [-0.00351099  0.01287482  0.00427162 ... -0.02073745  0.00202361
   0.04911081]
 ...
 [-0.00790145 -0.00978288 -0.01209345 ... -0.00599931  0.02479347
   0.06604502]
 [-0.02531665 -0.01046877 -0.00940448 ...  0.0043818   0.0159668
   0.07002115]
 [-0.0162943   0.01417718  0.00473878 ... -0.02351897  0.00884433
   0.03623604]]
In [12]:
    #algorithms=["KMeans", "ActivePCKMeans", "PCKMeans", "ConstrainedKMeans", "SeededKMeans"]
    algorithms=["GPTExpansionClustering"]
    #algorithms=["GPTExpansionClustering"]
    
    process_raw_data = args.dataset.endswith("-raw")
In [13]:
    results = compare_algorithms(features,
                                 documents,
                                 y,
                                 side_information,
                                 args.num_clusters,
                                 args.dataset,
                                 num_corrections=args.num_corrections,
                                 split=args.dataset_split,
                                 max_feedback_given=args.max_feedback_given,
                                 num_seeds=args.num_seeds,
                                 verbose=args.verbose,
                                 normalize_vectors=args.normalize_vectors,
                                 split_normalization = args.split_normalization,
                                 algorithms=algorithms,
                                 init=args.init,
                                 num_reinit=args.num_reinit,
                                 plot_clusters=args.plot_clusters,
                                 cluster_plot_dir_prefix=args.plot_dir,
                                 dataset = args.dataset,
                                 process_raw_data=process_raw_data,
                                 pckmeans_w = args.pckmeans_w)
    summarized_results = summarize_results(results)
    print(json.dumps(summarized_results, indent=2))
Starting comparison of 10 seeds:
Starting experiments for 0th seed
Running GPTExpansionClustering for seed 0
0it [00:00, ?it/s]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am still waiting for my card after 1 week.  Is this ok?"

Keyphrases:
15it [00:01, 10.99it/s]
ChatCompletion(id='chatcmpl-9My5eQ3RvCDowrxxIWcbDd6bNf20e', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery delay", "expected delivery time", "delayed card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261230, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=235, total_tokens=250))
["card delivery delay", "expected delivery time", "delayed card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why hasn't my card been delivered?"

Keyphrases:
18it [00:03,  4.47it/s]
ChatCompletion(id='chatcmpl-9My5f0iOn5yIfKIhLSgR7aOcSON3J', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery status", "undelivered card", "tracking card shipment"]', role='assistant', function_call=None, tool_calls=None))], created=1715261231, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["card delivery status", "undelivered card", "tracking card shipment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card still hasn't arrived after 2 weeks. Is it lost?"

Keyphrases:
20it [00:05,  2.76it/s]
ChatCompletion(id='chatcmpl-9My5h34Ht5UlI5Oar3aRS4WaEDjR4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card not received", "lost card", "delayed card delivery"]', role='assistant', function_call=None, tool_calls=None))], created=1715261233, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["card not received", "lost card", "delayed card delivery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long should my new card take to arrive?"

Keyphrases:
23it [00:08,  1.99it/s]
ChatCompletion(id='chatcmpl-9My5j4xDjP8zZXwB5fg92s8hC4uVx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery time", "new card ETA", "card arrival schedule"]', role='assistant', function_call=None, tool_calls=None))], created=1715261235, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["card delivery time", "new card ETA", "card arrival schedule"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card has not arrived yet, where is it?"

Keyphrases:
25it [00:09,  1.95it/s]
ChatCompletion(id='chatcmpl-9My5mkKXvqWtRM17zEGq5s7m21DWs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery status", "card shipment tracking", "missing card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261238, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["card delivery status", "card shipment tracking", "missing card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the tracking number for my card that was mailed?"

Keyphrases:
26it [00:11,  1.27it/s]
ChatCompletion(id='chatcmpl-9My5ner4WPlBU7l7ivGlCWFDW9O9k', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card tracking number", "mail tracking", "status of mailed card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261239, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["card tracking number", "mail tracking", "status of mailed card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I know when my card will arrive?"

Keyphrases:
33it [00:13,  2.13it/s]
ChatCompletion(id='chatcmpl-9My5qEZZMBX5no4Ur5n3wOoES6eS5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card arrival", "expected delivery date", "track card shipment"]', role='assistant', function_call=None, tool_calls=None))], created=1715261242, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["card arrival", "expected delivery date", "track card shipment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm starting to think my card is lost because it still hasn't arrived, can you help?"

Keyphrases:
37it [00:14,  2.31it/s]
ChatCompletion(id='chatcmpl-9My5rfeJXYP29XV0yD4iuugrb8L5F', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost card", "card not received", "card assistance"]', role='assistant', function_call=None, tool_calls=None))], created=1715261243, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=238, total_tokens=251))
["lost card", "card not received", "card assistance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there tracking info available?"

Keyphrases:
38it [00:16,  1.96it/s]
ChatCompletion(id='chatcmpl-9My5tlBhvbAd58C6DHwRogAY1ppmH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["tracking information", "package tracking", "order status"]', role='assistant', function_call=None, tool_calls=None))], created=1715261245, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["tracking information", "package tracking", "order status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is the tracking number for the card you sent me?"

Keyphrases:
40it [00:21,  1.02s/it]
ChatCompletion(id='chatcmpl-9My5uoBnYOzav0YGWBwHl63FaTFvP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["tracking number", "card shipment tracking", "shipment status"]', role='assistant', function_call=None, tool_calls=None))], created=1715261246, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["tracking number", "card shipment tracking", "shipment status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why won't my card show up on the app?"

Keyphrases:
41it [00:24,  1.26s/it]
ChatCompletion(id='chatcmpl-9My5zK8PvysgDxD001e2IKIEUlbsn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card visibility", "missing card in app", "app issue with card display"]', role='assistant', function_call=None, tool_calls=None))], created=1715261251, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["card visibility", "missing card in app", "app issue with card display"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to reactivate my card."

Keyphrases:
42it [00:25,  1.25s/it]
ChatCompletion(id='chatcmpl-9My62OKTiFFqbh6LRTIRSjk3gA9cs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reactivate card", "card activation", "enable card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261254, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["reactivate card", "card activation", "enable card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have received my card, can you help me put it in the app?"

Keyphrases:
44it [00:26,  1.05s/it]
ChatCompletion(id='chatcmpl-9My63nMv7JyVoKJi7X7kCuEn1DsyN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "add card to app", "register card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261255, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["card activation", "add card to app", "register card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I link a card that I already have?"

Keyphrases:
45it [00:28,  1.21s/it]
ChatCompletion(id='chatcmpl-9My65rKL399fkdAhIG7v8eyahXdYX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["link existing card", "add card", "card management"]', role='assistant', function_call=None, tool_calls=None))], created=1715261257, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["link existing card", "add card", "card management"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I received my new card, but I don't see it in the app anywhere.  What do I do?"

Keyphrases:
46it [00:35,  2.36s/it]
ChatCompletion(id='chatcmpl-9My66P7q1jCsHWBnIsNwS3mmskYZs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card not visible in app", "new card activation", "missing card in app"]', role='assistant', function_call=None, tool_calls=None))], created=1715261258, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=18, prompt_tokens=241, total_tokens=259))
["card not visible in app", "new card activation", "missing card in app"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I re-add a card to the app?"

Keyphrases:
47it [00:36,  2.11s/it]
ChatCompletion(id='chatcmpl-9My6DcFb8uudbe1bUYlIbXunKjctF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["re-add card", "add card again", "card management"]', role='assistant', function_call=None, tool_calls=None))], created=1715261265, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["re-add card", "add card again", "card management"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I add the card to my account?"

Keyphrases:
48it [00:39,  2.20s/it]
ChatCompletion(id='chatcmpl-9My6EWvE0BDZv40yg3ln998PUFb1v', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["add card", "link card", "card registration"]', role='assistant', function_call=None, tool_calls=None))], created=1715261266, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["add card", "link card", "card registration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I link a new card?"

Keyphrases:
51it [00:40,  1.30s/it]
ChatCompletion(id='chatcmpl-9My6HUt5EyEUniuDqO7ynptZpo6Cr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["link card", "add card", "add new card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261269, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["link card", "add card", "add new card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I link an existing card?"

Keyphrases:
52it [00:42,  1.38s/it]
ChatCompletion(id='chatcmpl-9My6IMntIOBwpMb97X4KZRJahG9bq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["link card", "add existing card", "card linkage"]', role='assistant', function_call=None, tool_calls=None))], created=1715261270, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["link card", "add existing card", "card linkage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hello, I found the card I misplaced and I need to reactive it, how do I do that?"

Keyphrases:
56it [00:45,  1.10s/it]
ChatCompletion(id='chatcmpl-9My6KVdWTTTbuZC0n1UhvM6mPeOdy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reactivate card", "found lost card", "card activation"]', role='assistant', function_call=None, tool_calls=None))], created=1715261272, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=239, total_tokens=253))
["reactivate card", "found lost card", "card activation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me how to link one of your cards that I already have?"

Keyphrases:
57it [00:47,  1.22s/it]
ChatCompletion(id='chatcmpl-9My6Nu00CvsNOuOOx9egpMxHV7NtY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["link card", "add existing card", "card linking process"]', role='assistant', function_call=None, tool_calls=None))], created=1715261275, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["link card", "add existing card", "card linking process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I view the card I received in the app?"

Keyphrases:
58it [00:48,  1.27s/it]
ChatCompletion(id='chatcmpl-9My6PhhxHpJT5fRnECEPHXPtUaohu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["view card", "card management", "access card in app"]', role='assistant', function_call=None, tool_calls=None))], created=1715261277, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["view card", "card management", "access card in app"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where on the website do I go to link my card?"

Keyphrases:
59it [00:50,  1.32s/it]
ChatCompletion(id='chatcmpl-9My6Rgft6zEIlAKd7v1oIPSdQCc65', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["link card", "card management", "website navigation"]', role='assistant', function_call=None, tool_calls=None))], created=1715261279, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["link card", "card management", "website navigation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I found my card, can I add it to the app?"

Keyphrases:
60it [00:52,  1.41s/it]
ChatCompletion(id='chatcmpl-9My6St1RtMWCBTAvx2I6CdEu8EnoD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["add card", "register card", "card setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715261280, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["add card", "register card", "card setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've received my card so now I need to know how to sync it to the app."

Keyphrases:
62it [00:53,  1.11s/it]
ChatCompletion(id='chatcmpl-9My6UOFca5YmnDNgRuS2tSvBHBezm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card synchronization", "sync card with app", "card setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715261282, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=237, total_tokens=251))
["card synchronization", "sync card with app", "card setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I found my card, I would like to reactivate it."

Keyphrases:
63it [00:56,  1.46s/it]
ChatCompletion(id='chatcmpl-9My6Vyb37OispM7YcJjUI4fFWiHpM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reactivate card", "card reactivation", "card found"]', role='assistant', function_call=None, tool_calls=None))], created=1715261283, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["reactivate card", "card reactivation", "card found"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I link this new card?"

Keyphrases:
64it [00:57,  1.52s/it]
ChatCompletion(id='chatcmpl-9My6YFVPrMKT8XoSSkaF1dW3M1BWw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["link new card", "add card", "card setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715261286, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["link new card", "add card", "card setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app doesn't show the card I received."

Keyphrases:
67it [01:00,  1.14s/it]
ChatCompletion(id='chatcmpl-9My6aQbwcB8HNI9XUieRQDUEIC05E', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["app issue", "card not showing", "technical problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715261288, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["app issue", "card not showing", "technical problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how do I link a card I already have?"

Keyphrases:
68it [01:01,  1.22s/it]
ChatCompletion(id='chatcmpl-9My6cDNac3JtII02DT0cyUlWZNw0L', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["link existing card", "add card to account", "card linkage"]', role='assistant', function_call=None, tool_calls=None))], created=1715261290, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["link existing card", "add card to account", "card linkage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to link my card. How do I do it?"

Keyphrases:
69it [01:03,  1.40s/it]
ChatCompletion(id='chatcmpl-9My6eAEo95aJtArn1S8ptPZTBzBEG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["link card", "add card", "card linkage"]', role='assistant', function_call=None, tool_calls=None))], created=1715261292, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["link card", "add card", "card linkage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a way to make my old card usable with the app?"

Keyphrases:
72it [01:05,  1.03it/s]
ChatCompletion(id='chatcmpl-9My6gYSkBUum3SqmZNfdDZC7VsjPp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card compatibility", "app integration", "using old card with app"]', role='assistant', function_call=None, tool_calls=None))], created=1715261294, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["card compatibility", "app integration", "using old card with app"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I need to go in the app to enter my card info?"

Keyphrases:
75it [01:07,  1.14it/s]
ChatCompletion(id='chatcmpl-9My6h7Fsf2SmRfhQEKaxYA3eaZSKM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card information entry", "update card details", "enter card info"]', role='assistant', function_call=None, tool_calls=None))], created=1715261295, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["card information entry", "update card details", "enter card info"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I already have one of your cards, how do I link them?"

Keyphrases:
78it [01:09,  1.35it/s]
ChatCompletion(id='chatcmpl-9My6j5fNAbbHDECiITk089OjFQ4Fg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["link cards", "card management", "add card to account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261297, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["link cards", "card management", "add card to account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I link my replacement card?"

Keyphrases:
79it [01:10,  1.10it/s]
ChatCompletion(id='chatcmpl-9My6lwCzkWLsCZn45spBw8kReWG72', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["link replacement card", "replacement card setup", "associate new card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261299, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["link replacement card", "replacement card setup", "associate new card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I link another card to my account?"

Keyphrases:
80it [01:12,  1.07s/it]
ChatCompletion(id='chatcmpl-9My6nRyIieIj0nkhTpvmFJifp1hK4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["link card", "add card", "additional card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261301, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["link card", "add card", "additional card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to know your exchange rates."

Keyphrases:
81it [01:14,  1.15s/it]
ChatCompletion(id='chatcmpl-9My6pdFZqywyHl0ecQ0opAEJA8jyX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rates", "currency conversion rates", "foreign exchange rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715261303, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["exchange rates", "currency conversion rates", "foreign exchange rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I find the exchange rate?"

Keyphrases:
85it [01:15,  1.44it/s]
ChatCompletion(id='chatcmpl-9My6qF17kXgpL9ejczApaHJeh2FxF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate", "currency conversion", "rate lookup"]', role='assistant', function_call=None, tool_calls=None))], created=1715261304, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["exchange rate", "currency conversion", "rate lookup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are your international exchange rates?"

Keyphrases:
86it [01:16,  1.21it/s]
ChatCompletion(id='chatcmpl-9My6ritzIP8ACIIZDuuSkz7Ojgsg2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rates", "currency conversion", "international rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715261305, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["exchange rates", "currency conversion", "international rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How are exchange rates calculated?"

Keyphrases:
89it [01:18,  1.53it/s]
ChatCompletion(id='chatcmpl-9My6tpvSu5QKkwZl8FnxepgUsiUnZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rates", "currency conversion", "rate calculation"]', role='assistant', function_call=None, tool_calls=None))], created=1715261307, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["exchange rates", "currency conversion", "rate calculation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what are exchange rates based on"

Keyphrases:
90it [01:19,  1.37it/s]
ChatCompletion(id='chatcmpl-9My6uJ6bJZNw8bipw4VeEI8vrfpii', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rates", "currency conversion factors", "basis of exchange rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715261308, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["exchange rates", "currency conversion factors", "basis of exchange rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the exchange rate like on this app?"

Keyphrases:
95it [01:20,  2.09it/s]
ChatCompletion(id='chatcmpl-9My6vxigdcNUsMyanKKb9ODCFGOm8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate", "currency conversion", "rate inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715261309, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["exchange rate", "currency conversion", "rate inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you have a list of exchange rates?"

Keyphrases:
96it [01:22,  1.41it/s]
ChatCompletion(id='chatcmpl-9My6wzYCZVaUW6FVy5AvjTXHaDTo0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rates", "currency conversion rates", "foreign exchange rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715261310, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["exchange rates", "currency conversion rates", "foreign exchange rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will I get a curreng foreign exchange rate?"

Keyphrases:
98it [01:24,  1.43it/s]
ChatCompletion(id='chatcmpl-9My6zi5KWJuZ4oDfazYVYHWXk2axO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign exchange rate", "current forex rate", "currency conversion rate"]', role='assistant', function_call=None, tool_calls=None))], created=1715261313, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["foreign exchange rate", "current forex rate", "currency conversion rate"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What currencies is an exchange rate calculated in?"

Keyphrases:
99it [01:25,  1.30it/s]
ChatCompletion(id='chatcmpl-9My70iLfSrk0TLgPeyUqLGeBaiKLM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate", "currency conversion", "currency types"]', role='assistant', function_call=None, tool_calls=None))], created=1715261314, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["exchange rate", "currency conversion", "currency types"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What exchange rate do you use?"

Keyphrases:
102it [01:26,  1.60it/s]
ChatCompletion(id='chatcmpl-9My71ILxnFm2ItFEnCLI55chjH8sS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate", "currency conversion", "transaction rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715261315, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["exchange rate", "currency conversion", "transaction rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The exchange rates are?"

Keyphrases:
103it [01:27,  1.42it/s]
ChatCompletion(id='chatcmpl-9My72CiE1sUBjfhphWp9YhH5si3um', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rates", "currency conversion", "current rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715261316, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["exchange rates", "currency conversion", "current rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What foreign exchange rate will you use?"

Keyphrases:
105it [01:29,  1.24it/s]
ChatCompletion(id='chatcmpl-9My73ScDMvDA4D9rsXwelEMfkT3rz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign exchange rate", "currency conversion rate", "exchange rate policy"]', role='assistant', function_call=None, tool_calls=None))], created=1715261317, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["foreign exchange rate", "currency conversion rate", "exchange rate policy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much will I get with the exchange rate?"

Keyphrases:
106it [01:30,  1.13it/s]
ChatCompletion(id='chatcmpl-9My75nfi7wG7bCzhjPEvuGfS3AhTa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate calculation", "currency conversion", "financial conversion rate"]', role='assistant', function_call=None, tool_calls=None))], created=1715261319, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["exchange rate calculation", "currency conversion", "financial conversion rate"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the exchange rate like?"

Keyphrases:
108it [01:31,  1.32it/s]
ChatCompletion(id='chatcmpl-9My77ycB5V0OagLP1zaqDLrdIhRtK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate", "currency conversion", "foreign exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715261321, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["exchange rate", "currency conversion", "foreign exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where did your guys exchange rates come from?"

Keyphrases:
111it [01:33,  1.46it/s]
ChatCompletion(id='chatcmpl-9My78B4ZnffyG1FuOSOzyIdPDu6vH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rates source", "currency exchange information", "exchange rate origin"]', role='assistant', function_call=None, tool_calls=None))], created=1715261322, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["exchange rates source", "currency exchange information", "exchange rate origin"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me the foreign exchange rate?"

Keyphrases:
115it [01:35,  1.75it/s]
ChatCompletion(id='chatcmpl-9My7ASwQWomNz2Is2wgFC2mam4agr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign exchange", "exchange rate", "currency conversion"]', role='assistant', function_call=None, tool_calls=None))], created=1715261324, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["foreign exchange", "exchange rate", "currency conversion"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What kind of foreign exchange rate will I get when I exchange my money?"

Keyphrases:
117it [01:36,  1.75it/s]
ChatCompletion(id='chatcmpl-9My7BCvZrExYb3OhDuBUwLsqTSdw3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign exchange rate", "currency exchange", "exchange rate query"]', role='assistant', function_call=None, tool_calls=None))], created=1715261325, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["foreign exchange rate", "currency exchange", "exchange rate query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the current exchange rate for me?"

Keyphrases:
120it [01:40,  1.22it/s]
ChatCompletion(id='chatcmpl-9My7CgsmJ95F4rws6cqODLh1OFdvv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate", "currency conversion rate", "current rate"]', role='assistant', function_call=None, tool_calls=None))], created=1715261326, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["exchange rate", "currency conversion rate", "current rate"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a currency exchange and think I was charged more than I should of been."

Keyphrases:
122it [01:42,  1.19it/s]
ChatCompletion(id='chatcmpl-9My7GxUsTjdEJ7hmQ4ogMmotRhKBs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange issue", "overcharged", "exchange rate problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715261330, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["currency exchange issue", "overcharged", "exchange rate problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "the card payment exchange rate is wrong"

Keyphrases:
123it [01:47,  1.45s/it]
ChatCompletion(id='chatcmpl-9My7IAiKoQiKHFNp39mokTrY2dANC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate error", "incorrect exchange rate", "payment exchange rate issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261332, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["exchange rate error", "incorrect exchange rate", "payment exchange rate issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The rate applied to my foreign purchase was incorrect"

Keyphrases:
128it [01:49,  1.06it/s]
ChatCompletion(id='chatcmpl-9My7Nnc3k9ly274HlmcdLslytcCAc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign transaction rate", "incorrect exchange rate", "exchange rate issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261337, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["foreign transaction rate", "incorrect exchange rate", "exchange rate issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My exchange went wrong. I swapped Russian Ruble for UK pounds and was charged too much."

Keyphrases:
130it [01:51,  1.05it/s]
ChatCompletion(id='chatcmpl-9My7PcWSHPYr4zRXydDKjRYPhV8wT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange issue", "incorrect exchange rate", "overcharged exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715261339, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=237, total_tokens=252))
["currency exchange issue", "incorrect exchange rate", "overcharged exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "You did not apply the correct exchange rate for an item that I bought."

Keyphrases:
131it [01:52,  1.01s/it]
ChatCompletion(id='chatcmpl-9My7RYZ2kpuRrZNTi9lTqFHREULpS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate issue", "incorrect exchange rate", "currency conversion error"]', role='assistant', function_call=None, tool_calls=None))], created=1715261341, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["exchange rate issue", "incorrect exchange rate", "currency conversion error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The rate for a currency exchange was wrong when I bought something."

Keyphrases:
133it [01:54,  1.04it/s]
ChatCompletion(id='chatcmpl-9My7TBbFwtJEatrvrtuHX2nSCssek', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange rate", "incorrect rate", "exchange issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261343, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["currency exchange rate", "incorrect rate", "exchange issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I bought something overseas and the wrong exchange rate is on my statement."

Keyphrases:
136it [01:55,  1.34it/s]
ChatCompletion(id='chatcmpl-9My7UTI0RHup2TreOVUPGgERMflQ1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect exchange rate", "foreign transaction error", "exchange rate dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715261344, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["incorrect exchange rate", "foreign transaction error", "exchange rate dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is your exchange rate for my card payment wrong"

Keyphrases:
138it [01:57,  1.26it/s]
ChatCompletion(id='chatcmpl-9My7Wt9MWKYgAHfr7bb40wuSWOM3G', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate issue", "incorrect exchange rate", "card payment rate error"]', role='assistant', function_call=None, tool_calls=None))], created=1715261346, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["exchange rate issue", "incorrect exchange rate", "card payment rate error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why am I being charged more ?"

Keyphrases:
139it [01:58,  1.13it/s]
ChatCompletion(id='chatcmpl-9My7YlVFRzUIOviWvryslmIec5aAA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra charges", "unexplained charges", "billing issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261348, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["extra charges", "unexplained charges", "billing issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When I made a purchase last Saturday, I was charged extra. Did I receive the right exchange rate?"

Keyphrases:
142it [02:00,  1.40it/s]
ChatCompletion(id='chatcmpl-9My7ZCb3Z6gMb0zvbRgm7r7uJvRnI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate issue", "incorrect charge", "purchase query"]', role='assistant', function_call=None, tool_calls=None))], created=1715261349, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=239, total_tokens=252))
["exchange rate issue", "incorrect charge", "purchase query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "They charged me wrong for a currency exchange on a purchase."

Keyphrases:
143it [02:03,  1.13s/it]
ChatCompletion(id='chatcmpl-9My7aXaI2qWOPk0S4nCNAXfap3txM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect charge", "currency exchange error", "transaction dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715261350, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["incorrect charge", "currency exchange error", "transaction dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I believe my card payment exchange rate is incorrect."

Keyphrases:
144it [02:04,  1.16s/it]
ChatCompletion(id='chatcmpl-9My7dFAqydtP3cjrhmuQ94qWw7ES9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate issue", "incorrect exchange rate", "card payment rate error"]', role='assistant', function_call=None, tool_calls=None))], created=1715261353, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["exchange rate issue", "incorrect exchange rate", "card payment rate error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hi, I have been overcharged for my payment last Saturday. I guess exchange rate was wrong."

Keyphrases:
145it [02:06,  1.24s/it]
ChatCompletion(id='chatcmpl-9My7fWydDnd9wYM3uYise2Fdt1nPq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["overcharged", "incorrect exchange rate", "payment dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715261355, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=238, total_tokens=251))
["overcharged", "incorrect exchange rate", "payment dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "the conversion value for my card payments is incorrect."

Keyphrases:
151it [02:08,  1.51it/s]
ChatCompletion(id='chatcmpl-9My7ggfND6wfh8JyUajpuz6xbW8UX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["conversion error", "incorrect payment conversion", "card payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261356, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["conversion error", "incorrect payment conversion", "card payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The wrong exchange rate was used when I bought something with a foriegn currency."

Keyphrases:
152it [02:09,  1.31it/s]
ChatCompletion(id='chatcmpl-9My7iL1ixJ0IznhGsdWjjpdHTfllY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect exchange rate", "foreign currency transaction", "exchange rate error"]', role='assistant', function_call=None, tool_calls=None))], created=1715261358, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=235, total_tokens=250))
["incorrect exchange rate", "foreign currency transaction", "exchange rate error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I check the exchange rate applied to my transaction?"

Keyphrases:
157it [02:11,  1.81it/s]
ChatCompletion(id='chatcmpl-9My7ki3C4Wp3QSULcS7Ak6rxULijY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate", "currency conversion details", "transaction details"]', role='assistant', function_call=None, tool_calls=None))], created=1715261360, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["exchange rate", "currency conversion details", "transaction details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Your exchange rate is totally wrong for my card payment"

Keyphrases:
158it [02:13,  1.52it/s]
ChatCompletion(id='chatcmpl-9My7lyXuJKXKnIZ2NxXOh2gilt7xD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate issue", "incorrect exchange rate", "card payment dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715261361, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["exchange rate issue", "incorrect exchange rate", "card payment dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My statement has a dollar I have been charged showing up on it."

Keyphrases:
161it [02:14,  1.78it/s]
ChatCompletion(id='chatcmpl-9My7n7gdtRH3mVJzb8QuGazVyv0fN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized charge", "statement inquiry", "billing dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715261363, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["unrecognized charge", "statement inquiry", "billing dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is there an extra dollar charged to my account?"

Keyphrases:
164it [02:15,  1.74it/s]
ChatCompletion(id='chatcmpl-9My7ogb8bZUNknqw7oHsfakTHolC4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unexplained charge", "account discrepancy", "extra charge inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715261364, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["unexplained charge", "account discrepancy", "extra charge inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you explain what this random $1 charge is?"

Keyphrases:
167it [02:18,  1.41it/s]
ChatCompletion(id='chatcmpl-9My7qTKFEvda0Ym58rc6gYdgGCuTU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unexplained charge", "transaction inquiry", "charge explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715261366, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["unexplained charge", "transaction inquiry", "charge explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why does my statement have these extra charges?"

Keyphrases:
169it [02:20,  1.39it/s]
ChatCompletion(id='chatcmpl-9My7tT85HUPTFF5hZAGQ0AyTUkegE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unexplained charges", "statement inquiry", "fee clarification"]', role='assistant', function_call=None, tool_calls=None))], created=1715261369, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["unexplained charges", "statement inquiry", "fee clarification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can see an extra 1£ charge on my app. Why did you charge me extra?"

Keyphrases:
171it [02:22,  1.19it/s]
ChatCompletion(id='chatcmpl-9My7vCSb2hevRu5s7ezvr4xfDQ0V8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra charge", "unexplained charge", "fee inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715261371, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=238, total_tokens=251))
["extra charge", "unexplained charge", "fee inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will the $1 transaction be credited to me?"

Keyphrases:
173it [02:24,  1.26it/s]
ChatCompletion(id='chatcmpl-9My7xkekJX3CTUGb7wuYH5PNeEoRH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction credit", "credit timing", "pending transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715261373, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["transaction credit", "credit timing", "pending transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where did this fee come from?"

Keyphrases:
174it [02:25,  1.09it/s]
ChatCompletion(id='chatcmpl-9My7yYxDs4vPeGBYTWj4vTqAjMNhp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fee origin", "unexplained charges", "transaction fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715261374, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["fee origin", "unexplained charges", "transaction fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I noticed an extra $1 charge on my statement, can you tell me why that is?"

Keyphrases:
175it [02:27,  1.08s/it]
ChatCompletion(id='chatcmpl-9My80qyek8QbhQDc2XqH99nBxO2YG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unexplained charge", "billing inquiry", "statement discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715261376, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=237, total_tokens=250))
["unexplained charge", "billing inquiry", "statement discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is an extra $1 charge"

Keyphrases:
176it [02:29,  1.18s/it]
ChatCompletion(id='chatcmpl-9My81YmU5dJgGrbePvqwGAvhDHRyP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra charge", "unexplained charge", "billing error"]', role='assistant', function_call=None, tool_calls=None))], created=1715261377, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["extra charge", "unexplained charge", "billing error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need information about an extra €1 fee in my statement."

Keyphrases:
177it [02:30,  1.23s/it]
ChatCompletion(id='chatcmpl-9My83tr2btqiTytnms8RBC2ezfYAA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra fee", "statement fee", "unknown charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715261379, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["extra fee", "statement fee", "unknown charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is there an extra 1 pound charge on my card?"

Keyphrases:
178it [02:32,  1.32s/it]
ChatCompletion(id='chatcmpl-9My84hPj52W4yovtD9tJbxW14uTZK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unexplained charge", "extra charge explanation", "card charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715261380, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["unexplained charge", "extra charge explanation", "card charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where did this 1 euro fee come from?"

Keyphrases:
181it [02:33,  1.17it/s]
ChatCompletion(id='chatcmpl-9My86nEktjHxbi0kRhO74IzqjmYFd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction fee", "unexplained charges", "fee inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715261382, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["transaction fee", "unexplained charges", "fee inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got a extra €1 fee in my statement"

Keyphrases:
182it [02:34,  1.05it/s]
ChatCompletion(id='chatcmpl-9My87VKvXpanmJCexJWvqHPy0dWMN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional fee", "fee complaint", "statement issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261383, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["additional fee", "fee complaint", "statement issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a 1 euro fee on my statement."

Keyphrases:
183it [02:36,  1.05s/it]
ChatCompletion(id='chatcmpl-9My882hMvsg3HJNv0JfpFZqAereph', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction fee", "account statement charge", "bank fee explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715261384, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["transaction fee", "account statement charge", "bank fee explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I overcharged a pound!?"

Keyphrases:
184it [02:37,  1.19s/it]
ChatCompletion(id='chatcmpl-9My8ALajNShOawzvunB0QByyyvq8K', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["overcharge issue", "incorrect charge", "billing error"]', role='assistant', function_call=None, tool_calls=None))], created=1715261386, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["overcharge issue", "incorrect charge", "billing error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where did the extra fee on my statement come from?"

Keyphrases:
186it [02:38,  1.08it/s]
ChatCompletion(id='chatcmpl-9My8CD4P5Hl0YqZZEMNohlTU9XCJ4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fee explanation", "statement inquiry", "additional charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715261388, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["fee explanation", "statement inquiry", "additional charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am seeing an extra fee on my statement what is that for?"

Keyphrases:
188it [02:40,  1.15it/s]
ChatCompletion(id='chatcmpl-9My8Dr8ZLj8pSjJl3GsJJx2bTlR04', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra fee explanation", "statement inquiry", "fee details"]', role='assistant', function_call=None, tool_calls=None))], created=1715261389, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["extra fee explanation", "statement inquiry", "fee details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am a new customer, and I happened to look at my app and there is a charge I am not familiar with.  Could you tell me why the extra charge is there?"

Keyphrases:
190it [02:41,  1.26it/s]
ChatCompletion(id='chatcmpl-9My8ErR3qcc09Pz3HwVE2ymgiL6ww', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized charge", "dispute transaction", "query charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715261390, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=255, total_tokens=269))
["unrecognized charge", "dispute transaction", "query charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a transaction for $1 and I don't know why it was charged."

Keyphrases:
192it [02:42,  1.37it/s]
ChatCompletion(id='chatcmpl-9My8FKG8S9rJMLaEdCXIh9etbCerg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "charge dispute", "transaction query"]', role='assistant', function_call=None, tool_calls=None))], created=1715261391, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=235, total_tokens=248))
["unrecognized transaction", "charge dispute", "transaction query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you help me with a weird charge?  It's a pound charge that never goes away from the statement view on the app I'm using.  It's not described as anything but "Pending", and that status has never changed during the last two days."

Keyphrases:
193it [02:44,  1.02it/s]
ChatCompletion(id='chatcmpl-9My8H2motZWbIt7PNfi31z6Gg7fbz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized charge", "pending transaction", "charge dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715261393, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=271, total_tokens=284))
["unrecognized charge", "pending transaction", "charge dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the extra  €1 fee in my statement"

Keyphrases:
196it [02:46,  1.24it/s]
ChatCompletion(id='chatcmpl-9My8Jc8CyekpxhHCEJ9vA5soshnFH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fee explanation", "statement inquiry", "unexplained charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715261395, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["fee explanation", "statement inquiry", "unexplained charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It's been two weeks, why has the transaction for $1.00 not been reversed?"

Keyphrases:
197it [02:48,  1.07it/s]
ChatCompletion(id='chatcmpl-9My8LNWPCOMQApOLw0VvQGUiksiMb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction reversal", "pending transaction", "delayed reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715261397, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=237, total_tokens=250))
["transaction reversal", "pending transaction", "delayed reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the €1 fee for?"

Keyphrases:
198it [02:51,  1.37s/it]
ChatCompletion(id='chatcmpl-9My8MolAhbZYb38xirCndflMqp5Wm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction fee", "service charge", "fee explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715261398, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["transaction fee", "service charge", "fee explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm quite confused as to what is going on. There is some odd extra pound charge on my statement in the app that's just listed as pending and doesn't go away since a couple days."

Keyphrases:
199it [02:56,  2.27s/it]
ChatCompletion(id='chatcmpl-9My8PExzGbSzGD1wXt8SG5e3nD6BM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending charges", "unexplained charges", "statement discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715261401, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=258, total_tokens=271))
["pending charges", "unexplained charges", "statement discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you please check why I am having this extra fee on my statement."

Keyphrases:
200it [02:58,  2.22s/it]
ChatCompletion(id='chatcmpl-9My8UifsgbnMgdVrs4BuxlSCIibYV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra fee explanation", "statement issue", "fee inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715261406, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["extra fee explanation", "statement issue", "fee inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transaction is still showing that is pending from my cash withdrawal."

Keyphrases:
203it [03:00,  1.39s/it]
ChatCompletion(id='chatcmpl-9My8XRcToyQRIgS7SvBHso9il87Y8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transaction", "cash withdrawal status", "transaction delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715261409, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["pending transaction", "cash withdrawal status", "transaction delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does the cash withdrawal take to pend?"

Keyphrases:
205it [03:02,  1.20s/it]
ChatCompletion(id='chatcmpl-9My8Yor6q7sXLgRv9AakvXI3WbPhx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal status", "pending withdrawal time", "withdrawal processing time"]', role='assistant', function_call=None, tool_calls=None))], created=1715261410, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["cash withdrawal status", "pending withdrawal time", "withdrawal processing time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried taking money from the ATM but no money came out, but the transaction is still pending? How is this possible?"

Keyphrases:
207it [03:03,  1.03s/it]
ChatCompletion(id='chatcmpl-9My8aVSFRhbekx2SQv6pVRPqT9KIe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "transaction pending", "withdrawal failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715261412, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=243, total_tokens=257))
["ATM issue", "transaction pending", "withdrawal failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got some cash of an ATM earlier but this shows up as pending in the app. How can this be still pending, I've got the cash already?"

Keyphrases:
208it [03:07,  1.64s/it]
ChatCompletion(id='chatcmpl-9My8bqG5SvxCUcVhA5XxjDvFhS1rN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transaction", "ATM withdrawal status", "transaction status"]', role='assistant', function_call=None, tool_calls=None))], created=1715261413, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=250, total_tokens=264))
["pending transaction", "ATM withdrawal status", "transaction status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my withdrawal still pending?"

Keyphrases:
209it [03:10,  1.78s/it]
ChatCompletion(id='chatcmpl-9My8gyHdqTQ0lzpQEhqi1QB0mex9H', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending withdrawal", "withdrawal status", "delayed withdrawal"]', role='assistant', function_call=None, tool_calls=None))], created=1715261418, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["pending withdrawal", "withdrawal status", "delayed withdrawal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are you sure when the withdrawal will show?"

Keyphrases:
210it [03:11,  1.64s/it]
ChatCompletion(id='chatcmpl-9My8i48PL8jw4BVzKS2i7mBD9DOiR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal status", "fund availability", "withdrawal timing"]', role='assistant', function_call=None, tool_calls=None))], created=1715261420, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["withdrawal status", "fund availability", "withdrawal timing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "my atm cash out is still pending"

Keyphrases:
214it [03:12,  1.07it/s]
ChatCompletion(id='chatcmpl-9My8jJNMWdVdCChCsGyqJyQYzdiY8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal status", "pending cash withdrawal", "ATM transaction delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715261421, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["ATM withdrawal status", "pending cash withdrawal", "ATM transaction delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am still waiting for a cash withdrawal to show"

Keyphrases:
215it [03:14,  1.00it/s]
ChatCompletion(id='chatcmpl-9My8lXgmyZfLPinGIBW8P6p6FxuZP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending withdrawal", "withdrawal status", "cash withdrawal delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715261423, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["pending withdrawal", "withdrawal status", "cash withdrawal delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is my pending cash withdrawal processed?"

Keyphrases:
216it [03:16,  1.33s/it]
ChatCompletion(id='chatcmpl-9My8mlO12rVTgeEjrcvHmdFj6bc1t', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending withdrawal", "withdrawal status", "cash withdrawal processing"]', role='assistant', function_call=None, tool_calls=None))], created=1715261424, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["pending withdrawal", "withdrawal status", "cash withdrawal processing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my ATM cash withdrawal showing up as a pending transaction?"

Keyphrases:
218it [03:18,  1.20s/it]
ChatCompletion(id='chatcmpl-9My8p99YsUmNQ1fDKM0BSmDnudRdJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transaction", "ATM withdrawal status", "cash withdrawal query"]', role='assistant', function_call=None, tool_calls=None))], created=1715261427, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["pending transaction", "ATM withdrawal status", "cash withdrawal query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do I have a pending cash withdrawal?"

Keyphrases:
221it [03:20,  1.12it/s]
ChatCompletion(id='chatcmpl-9My8rYueKnVng6hIa40K3Cu4OVS6A', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending withdrawal", "cash withdrawal status", "withdrawal issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261429, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["pending withdrawal", "cash withdrawal status", "withdrawal issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is my cash withdrawal pending?"

Keyphrases:
224it [03:23,  1.05it/s]
ChatCompletion(id='chatcmpl-9My8smwBxDUBeK38kB3LJ9fcFgKBw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal status", "pending withdrawal", "withdrawal inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715261430, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["cash withdrawal status", "pending withdrawal", "withdrawal inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm not quite understanding why my cash withdrawal is showing as pending."

Keyphrases:
225it [03:24,  1.00it/s]
ChatCompletion(id='chatcmpl-9My8vkSAGlSmU3DjwuK6HpBkHwrUk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending withdrawal", "withdrawal status", "cash withdrawal issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261433, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["pending withdrawal", "withdrawal status", "cash withdrawal issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why does my account have a pending cash withdrawal?"

Keyphrases:
229it [03:26,  1.29it/s]
ChatCompletion(id='chatcmpl-9My8xDtngXXb8D8BsRS7HeqeDtbKd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending withdrawal", "account status", "cash withdrawal status"]', role='assistant', function_call=None, tool_calls=None))], created=1715261435, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["pending withdrawal", "account status", "cash withdrawal status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to take money from my card, but it didn't work. Later I saw that the transaction is still in progress. What's goign on?"

Keyphrases:
233it [03:28,  1.65it/s]
ChatCompletion(id='chatcmpl-9My8zypstMBTPYb8jYMy9X6CiZb9S', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction status", "pending transaction", "withdrawal issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261437, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=250, total_tokens=263))
["transaction status", "pending transaction", "withdrawal issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where's accounting for my cash withdrawal?"

Keyphrases:
236it [03:30,  1.46it/s]
ChatCompletion(id='chatcmpl-9My90N6VxHvHu8XiO5KQPL47fox4D', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal tracking", "withdrawal statement", "transaction history"]', role='assistant', function_call=None, tool_calls=None))], created=1715261438, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["cash withdrawal tracking", "withdrawal statement", "transaction history"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My account was charged for a withdraw I tried to make that was decline."

Keyphrases:
237it [03:33,  1.01it/s]
ChatCompletion(id='chatcmpl-9My93DKbqgFwy6Gf09Kx89M6U9qKK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal charge", "declined withdrawal", "unauthorized charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715261441, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["withdrawal charge", "declined withdrawal", "unauthorized charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my cash withdrawal from the ATM still not yet showing as confirmed in my account?"

Keyphrases:
239it [03:36,  1.04s/it]
ChatCompletion(id='chatcmpl-9My96zLJAgSfeEke49rBWBMSNFFUv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal", "withdrawal confirmation", "transaction status"]', role='assistant', function_call=None, tool_calls=None))], created=1715261444, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=236, total_tokens=250))
["ATM withdrawal", "withdrawal confirmation", "transaction status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What's a pending transaction? My card was declined at an ATM, but my account says it's still pending. Can I cancel the payment?"

Keyphrases:
240it [03:38,  1.17s/it]
ChatCompletion(id='chatcmpl-9My98rWFjBdoUcvCE4D4g8ULkwLXW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transaction", "card declined", "cancel payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715261446, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=247, total_tokens=259))
["pending transaction", "card declined", "cancel payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to know how many different currencies my money can be in"

Keyphrases:
242it [03:39,  1.00s/it]
ChatCompletion(id='chatcmpl-9My9AyQdbsS0G9OwA2TAVBmLKCjax', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency options", "multiple currencies", "account currency diversity"]', role='assistant', function_call=None, tool_calls=None))], created=1715261448, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["currency options", "multiple currencies", "account currency diversity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you support all fiat currencies?"

Keyphrases:
243it [03:40,  1.04s/it]
ChatCompletion(id='chatcmpl-9My9BnpnQLRr8LwHItZMxwaENxxxK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency support", "fiat currency", "supported currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715261449, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["currency support", "fiat currency", "supported currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What currencies do you do exchanges for?"

Keyphrases:
248it [03:42,  1.44it/s]
ChatCompletion(id='chatcmpl-9My9Cs3Z3MFZODlVZINu378dQxx0q', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "foreign exchange", "available currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715261450, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["currency exchange", "foreign exchange", "available currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "In terms of holding and exchange, what fiat currencies do you use."

Keyphrases:
249it [03:45,  1.02it/s]
ChatCompletion(id='chatcmpl-9My9FH07tbWueDxJqO5usGY76MrQ1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fiat currencies", "currency exchange", "holding requirements"]', role='assistant', function_call=None, tool_calls=None))], created=1715261453, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["fiat currencies", "currency exchange", "holding requirements"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What fiat currencies are used for holding transactions?"

Keyphrases:
250it [03:47,  1.07s/it]
ChatCompletion(id='chatcmpl-9My9HUYWx7FMQpGRokZsHpm84FPL3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fiat currencies", "currency types", "transaction currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715261455, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["fiat currencies", "currency types", "transaction currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I exchange my money for EUR?"

Keyphrases:
251it [03:48,  1.09s/it]
ChatCompletion(id='chatcmpl-9My9Jmy6ag0rFF34EvGdfim9j9VVZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange location", "EUR exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715261457, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["currency exchange", "exchange location", "EUR exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I change currencies to euros?"

Keyphrases:
256it [03:50,  1.29it/s]
ChatCompletion(id='chatcmpl-9My9K01y2I7VhxPZrYH9TraJn2Cff', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "change to euros", "forex transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715261458, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["currency exchange", "change to euros", "forex transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What fiat currencies are supported for holding and exchange?"

Keyphrases:
257it [03:52,  1.18it/s]
ChatCompletion(id='chatcmpl-9My9Nn0KEwpsO5hcUCNNxjfLHn8Eb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported currencies", "currency exchange", "fiat currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715261461, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["supported currencies", "currency exchange", "fiat currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When considering currency holdings and exchanges, what fiat currencies are supported?"

Keyphrases:
258it [03:54,  1.11s/it]
ChatCompletion(id='chatcmpl-9My9Oeb6lbPDFdgUPZ1ehqkQjMpwC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported currencies", "currency exchange", "fiat currency options"]', role='assistant', function_call=None, tool_calls=None))], created=1715261462, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["supported currencies", "currency exchange", "fiat currency options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What options do I have for holding currencies?"

Keyphrases:
261it [03:56,  1.13it/s]
ChatCompletion(id='chatcmpl-9My9QntUPLALnkCZhKqNmTXFyXTTF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency options", "holding currencies", "multi-currency account options"]', role='assistant', function_call=None, tool_calls=None))], created=1715261464, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["currency options", "holding currencies", "multi-currency account options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you accept exchanges to EUR?"

Keyphrases:
263it [03:57,  1.25it/s]
ChatCompletion(id='chatcmpl-9My9SiMtoCcFBy6PFPTu4PjVHUpag', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "EUR exchange", "exchange rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715261466, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["currency exchange", "EUR exchange", "exchange rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What currencies are used in your exchange?"

Keyphrases:
266it [03:59,  1.26it/s]
ChatCompletion(id='chatcmpl-9My9T3g8ENGF9WR0YkZnTzBrcXuAX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "available currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715261467, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["currency exchange", "exchange rates", "available currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Which fiat currencies do you support?"

Keyphrases:
267it [04:01,  1.11it/s]
ChatCompletion(id='chatcmpl-9My9WeRFFBgukFgroP0UTJo3OYizv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported currencies", "fiat currency support", "available currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715261470, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["supported currencies", "fiat currency support", "available currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to make a currency exchange to EU."

Keyphrases:
269it [04:02,  1.18it/s]
ChatCompletion(id='chatcmpl-9My9XHhVDsDECbMbhq3TwqdN5wsTx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "foreign currency transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715261471, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["currency exchange", "exchange rates", "foreign currency transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I exchange currencies?"

Keyphrases:
272it [04:04,  1.46it/s]
ChatCompletion(id='chatcmpl-9My9ZJpBPSqTHQmrpvydtBg0aJ11n', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "foreign exchange", "exchange rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715261473, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["currency exchange", "foreign exchange", "exchange rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you work with all fiat currencies?"

Keyphrases:
273it [04:06,  1.04it/s]
ChatCompletion(id='chatcmpl-9My9amAAnXUTpA2IdvIAVBcaUFsJ6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fiat currencies support", "currency compatibility", "supported currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715261474, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["fiat currencies support", "currency compatibility", "supported currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I hold money in multiple currencies?"

Keyphrases:
274it [04:07,  1.01s/it]
ChatCompletion(id='chatcmpl-9My9cwRoFnCtG8NJvnHEjesfNg2O5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple currencies", "currency holding", "foreign currency account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261476, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["multiple currencies", "currency holding", "foreign currency account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How man currencies can I hold?"

Keyphrases:
275it [04:10,  1.26s/it]
ChatCompletion(id='chatcmpl-9My9eOzmR3uPcVKr0QDl7NXQW8EpI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multi-currency account", "currency options", "number of currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715261478, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["multi-currency account", "currency options", "number of currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I accept exchanges to EU?"

Keyphrases:
277it [04:11,  1.11s/it]
ChatCompletion(id='chatcmpl-9My9gxBI7FB8Xe1xdmh728CDpQlU4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange policy", "accept exchanges", "EU exchanges"]', role='assistant', function_call=None, tool_calls=None))], created=1715261480, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["exchange policy", "accept exchanges", "EU exchanges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What kind of fiat currency can I used for holding and exchange?"

Keyphrases:
278it [04:12,  1.14s/it]
ChatCompletion(id='chatcmpl-9My9hxZbYvLoXAa0ASXmSsdS6l3ZJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fiat currency options", "currency types", "available currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715261481, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["fiat currency options", "currency types", "available currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "i need my card quick"

Keyphrases:
283it [04:14,  1.69it/s]
ChatCompletion(id='chatcmpl-9My9jFBlOKW6TCUIVrIo7ZvKK5K6n', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["urgent card request", "expedite card", "fast card delivery"]', role='assistant', function_call=None, tool_calls=None))], created=1715261483, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=224, total_tokens=240))
["urgent card request", "expedite card", "fast card delivery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long will it take to get to me?"

Keyphrases:
284it [04:15,  1.37it/s]
ChatCompletion(id='chatcmpl-9My9kZ15ZK95GcHzgt1bGcbL7XyWh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["delivery time", "shipment duration", "arrival time"]', role='assistant', function_call=None, tool_calls=None))], created=1715261484, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["delivery time", "shipment duration", "arrival time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long will it take to deliver something to US?"

Keyphrases:
287it [04:17,  1.47it/s]
ChatCompletion(id='chatcmpl-9My9lUwX2gsUJJyuGRzFMBaOWTELz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["delivery duration", "shipment time", "time to deliver to US"]', role='assistant', function_call=None, tool_calls=None))], created=1715261485, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["delivery duration", "shipment time", "time to deliver to US"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When can I expect my card to be delivered to the US?"

Keyphrases:
289it [04:19,  1.40it/s]
ChatCompletion(id='chatcmpl-9My9nPAzyuvtepwhG76sjl5PkzVvv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery time", "expected delivery date", "US card delivery"]', role='assistant', function_call=None, tool_calls=None))], created=1715261487, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["card delivery time", "expected delivery date", "US card delivery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need my card quickly"

Keyphrases:
290it [04:22,  1.09s/it]
ChatCompletion(id='chatcmpl-9My9p9BNhvhw2Qsrma1VZffw5Koz2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["expedite card", "urgent card request", "fast card delivery"]', role='assistant', function_call=None, tool_calls=None))], created=1715261489, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=224, total_tokens=240))
["expedite card", "urgent card request", "fast card delivery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Does delivery to the US take long?"

Keyphrases:
291it [04:24,  1.32s/it]
ChatCompletion(id='chatcmpl-9My9s9te8KxMGwOloiryiNRk7aq4n', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["US delivery time", "delivery duration", "international shipping time"]', role='assistant', function_call=None, tool_calls=None))], created=1715261492, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["US delivery time", "delivery duration", "international shipping time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long will it take to arrive?"

Keyphrases:
292it [04:26,  1.43s/it]
ChatCompletion(id='chatcmpl-9My9uJPum6MJrUD1AYu3RscjyTu0d', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["delivery time", "ETA", "arrival time"]', role='assistant', function_call=None, tool_calls=None))], created=1715261494, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=11, prompt_tokens=226, total_tokens=237))
["delivery time", "ETA", "arrival time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the difference between standard and express delivery?"

Keyphrases:
294it [04:29,  1.50s/it]
ChatCompletion(id='chatcmpl-9My9wvi6KgIHAEMlXQT3OgPLnjw2p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["delivery options", "standard vs express", "shipping types"]', role='assistant', function_call=None, tool_calls=None))], created=1715261496, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["delivery options", "standard vs express", "shipping types"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "May I choose when it's delivered?"

Keyphrases:
296it [04:30,  1.22s/it]
ChatCompletion(id='chatcmpl-9My9zOkD26I4gU1S9EP7orn7pXdOA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["delivery scheduling", "choose delivery time", "set delivery date"]', role='assistant', function_call=None, tool_calls=None))], created=1715261499, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["delivery scheduling", "choose delivery time", "set delivery date"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need it delivered on a certain date."

Keyphrases:
297it [04:32,  1.32s/it]
ChatCompletion(id='chatcmpl-9MyA1wW0s8FGKDJMCux9M2b0zW6uf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["specific delivery date", "schedule delivery", "delivery request"]', role='assistant', function_call=None, tool_calls=None))], created=1715261501, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["specific delivery date", "schedule delivery", "delivery request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When should I expect my card?"

Keyphrases:
298it [04:34,  1.39s/it]
ChatCompletion(id='chatcmpl-9MyA2nJtTPTaQun8pZ5yOxkqkq0Qc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery time", "expected card arrival", "when will card arrive"]', role='assistant', function_call=None, tool_calls=None))], created=1715261502, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["card delivery time", "expected card arrival", "when will card arrive"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long will it take for the card to arrive?"

Keyphrases:
300it [04:36,  1.23s/it]
ChatCompletion(id='chatcmpl-9MyA42iiLe5weWEXn7hpYYrxL9LJq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card arrival time", "expected delivery", "shipping duration"]', role='assistant', function_call=None, tool_calls=None))], created=1715261504, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["card arrival time", "expected delivery", "shipping duration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will the card arrive?"

Keyphrases:
305it [04:37,  1.44it/s]
ChatCompletion(id='chatcmpl-9MyA6wng7Uh74zsvLq3sTosGANr2K', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card arrival", "delivery status", "ETA of card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261506, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["card arrival", "delivery status", "ETA of card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When are cards delivered?"

Keyphrases:
307it [04:40,  1.20it/s]
ChatCompletion(id='chatcmpl-9MyA7Si2jtxPm5VtGeCFs8Q4SZPdr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery time", "delivery schedule", "when cards arrive"]', role='assistant', function_call=None, tool_calls=None))], created=1715261507, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=223, total_tokens=237))
["card delivery time", "delivery schedule", "when cards arrive"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does shipping take to get to a US destination?"

Keyphrases:
308it [04:41,  1.10it/s]
ChatCompletion(id='chatcmpl-9MyAAWweUscXZLlN0IlZbsOLDgIoe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["shipping duration", "US shipping time", "delivery estimate"]', role='assistant', function_call=None, tool_calls=None))], created=1715261510, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["shipping duration", "US shipping time", "delivery estimate"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get my card expedited?"

Keyphrases:
309it [04:42,  1.01it/s]
ChatCompletion(id='chatcmpl-9MyAB5SogR6qShst6zvAdWFNzrpDY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["expedited delivery", "fast card issuance", "speed up card delivery"]', role='assistant', function_call=None, tool_calls=None))], created=1715261511, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["expedited delivery", "fast card issuance", "speed up card delivery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long until my card is delivered?"

Keyphrases:
310it [04:44,  1.07s/it]
ChatCompletion(id='chatcmpl-9MyADwHxdF2HXWWBRAGLI9rStvidr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery time", "delivery ETA", "time until card arrival"]', role='assistant', function_call=None, tool_calls=None))], created=1715261513, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["card delivery time", "delivery ETA", "time until card arrival"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need my card to come as soon as possible."

Keyphrases:
311it [04:46,  1.31s/it]
ChatCompletion(id='chatcmpl-9MyAE8sRFRy6pqJp68Sxj0fkNfLf6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["expedite card delivery", "rush card delivery", "urgent card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715261514, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["expedite card delivery", "rush card delivery", "urgent card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When can I expect to receive my new card?"

Keyphrases:
312it [04:47,  1.31s/it]
ChatCompletion(id='chatcmpl-9MyAGnuxhfObPM2vwT94VKEpYptsG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery time", "new card ETA", "expected delivery date for card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261516, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["card delivery time", "new card ETA", "expected delivery date for card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am waiting for my card to arrive."

Keyphrases:
313it [04:49,  1.40s/it]
ChatCompletion(id='chatcmpl-9MyAIEJ0Dc2JoWMwSXIpe1wVJ4vVc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card arrival", "waiting for card", "card delivery status"]', role='assistant', function_call=None, tool_calls=None))], created=1715261518, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["card arrival", "waiting for card", "card delivery status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need my card as soon as possible."

Keyphrases:
314it [04:51,  1.65s/it]
ChatCompletion(id='chatcmpl-9MyAJ8usyhscIxQ5LMcmZnJZzxIz9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["urgent card request", "expedite card", "card delivery urgency"]', role='assistant', function_call=None, tool_calls=None))], created=1715261519, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["urgent card request", "expedite card", "card delivery urgency"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need it delivered by Saturday."

Keyphrases:
315it [04:53,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyAMjjLz3jJR1zyQHFFyOb8euhvp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["specific delivery request", "urgent delivery", "delivery deadline"]', role='assistant', function_call=None, tool_calls=None))], created=1715261522, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["specific delivery request", "urgent delivery", "delivery deadline"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What's the U.S. Delivery time?"

Keyphrases:
316it [04:54,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyANqjWfvuc2t9k4M75JLlxF4Grt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["U.S. delivery time", "delivery estimate", "shipping duration"]', role='assistant', function_call=None, tool_calls=None))], created=1715261523, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["U.S. delivery time", "delivery estimate", "shipping duration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will my card arrive?"

Keyphrases:
317it [04:56,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyAOMAxBqyUmZIfMCkTbKsJ1DB5E', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card arrival time", "expected delivery date", "when card delivered"]', role='assistant', function_call=None, tool_calls=None))], created=1715261524, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["card arrival time", "expected delivery date", "when card delivered"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "can I choose a date for delivery?"

Keyphrases:
318it [04:58,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyAQDTxtBeh7IW1bFwB7VT3C2PfO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["select delivery date", "schedule card delivery", "choose delivery time"]', role='assistant', function_call=None, tool_calls=None))], created=1715261526, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["select delivery date", "schedule card delivery", "choose delivery time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I make sure my card is delivered on a specific day?"

Keyphrases:
319it [05:00,  1.69s/it]
ChatCompletion(id='chatcmpl-9MyASAdTH8Bz3nHSuNjD9Sl1vjmbK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["specific delivery date", "card delivery scheduling", "schedule card delivery"]', role='assistant', function_call=None, tool_calls=None))], created=1715261528, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["specific delivery date", "card delivery scheduling", "schedule card delivery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I have it be delivered at a certain time?"

Keyphrases:
320it [05:01,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyAUXAQq8LN87jlVzIyiJv8nriBJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["specific delivery time", "time-based delivery", "delivery scheduling"]', role='assistant', function_call=None, tool_calls=None))], created=1715261530, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["specific delivery time", "time-based delivery", "delivery scheduling"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When traveling, can I auto top-up my card at certain times?"

Keyphrases:
321it [05:02,  1.50s/it]
ChatCompletion(id='chatcmpl-9MyAVQwWc7ICgxc1U2gm353y7fWKO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top-up", "travel card management", "scheduled top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715261531, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["auto top-up", "travel card management", "scheduled top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a limit when using auto top-up?"

Keyphrases:
322it [05:03,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyAWuBq9F70N3KewNcclSXAbqBb7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top-up limit", "top-up restrictions", "transaction limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715261532, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["auto top-up limit", "top-up restrictions", "transaction limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will it automatically top-up or do I need to do that manually if there isn't much cash left?"

Keyphrases:
323it [05:05,  1.53s/it]
ChatCompletion(id='chatcmpl-9MyAYlLX46chkwlixI7rBSx3nfKJr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["automatic top-up", "manual reload", "low balance action"]', role='assistant', function_call=None, tool_calls=None))], created=1715261534, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=239, total_tokens=253))
["automatic top-up", "manual reload", "low balance action"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm running out of money, can I  auto top up?"

Keyphrases:
324it [05:06,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyAZw60VSJ0eGN3vDKOViQydUsSy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top up", "low balance", "automatic reload"]', role='assistant', function_call=None, tool_calls=None))], created=1715261535, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["auto top up", "low balance", "automatic reload"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I use auto top up?"

Keyphrases:
325it [05:09,  1.68s/it]
ChatCompletion(id='chatcmpl-9MyAb1BKZGGay1BwRtGAu3fY7bXYz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top up", "set up auto reload", "automatic balance replenishment"]', role='assistant', function_call=None, tool_calls=None))], created=1715261537, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["auto top up", "set up auto reload", "automatic balance replenishment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can it automatically top-up money if there isn't much left?"

Keyphrases:
326it [05:11,  1.80s/it]
ChatCompletion(id='chatcmpl-9MyAdEAc19OJC4IeIsetzofTrgOdL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["automatic top-up", "low balance top-up", "auto-recharge"]', role='assistant', function_call=None, tool_calls=None))], created=1715261539, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["automatic top-up", "low balance top-up", "auto-recharge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If there isn't much money left can it automatically top-up?"

Keyphrases:
327it [05:12,  1.72s/it]
ChatCompletion(id='chatcmpl-9MyAfgYduqRoJjfeHL2HcckzLpMOz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["automatic top-up", "low balance", "auto-recharge"]', role='assistant', function_call=None, tool_calls=None))], created=1715261541, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["automatic top-up", "low balance", "auto-recharge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I read about the auto-top up function, but can't find it in the app."

Keyphrases:
328it [05:16,  2.44s/it]
ChatCompletion(id='chatcmpl-9MyAhIQCEUJ4zCfjTU03YOyl3NYh8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto-top up", "missing feature", "app functionality"]', role='assistant', function_call=None, tool_calls=None))], created=1715261543, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=236, total_tokens=249))
["auto-top up", "missing feature", "app functionality"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I have it add money at certain time intervals when I travel?"

Keyphrases:
329it [05:20,  2.73s/it]
ChatCompletion(id='chatcmpl-9MyAl6F7BUTpYNiTR7KjDwuRVFwsh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["scheduled transfers", "automatic deposits", "recurring transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715261547, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["scheduled transfers", "automatic deposits", "recurring transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm going to be away for awhile, can I have it add money automatically in certain intervals?"

Keyphrases:
330it [05:22,  2.46s/it]
ChatCompletion(id='chatcmpl-9MyApOYTLBvMuJnmjos4ClK5tqPPe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["scheduled transfers", "automatic deposits", "recurring payments"]', role='assistant', function_call=None, tool_calls=None))], created=1715261551, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=238, total_tokens=251))
["scheduled transfers", "automatic deposits", "recurring payments"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I find the "auto-top" feature?"

Keyphrases:
331it [05:24,  2.57s/it]
ChatCompletion(id='chatcmpl-9MyArbtjDDuMumZ7QbIgfAT0YneP9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto-top feature location", "find feature", "feature accessibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715261553, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["auto-top feature location", "find feature", "feature accessibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I just activated auto top-up, but it is not letting me enable it. Why not?"

Keyphrases:
332it [05:26,  2.33s/it]
ChatCompletion(id='chatcmpl-9MyAtbKQGiu9iUcFhoSXLmv3X7CkO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top-up issue", "top-up activation problem", "enable auto top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715261555, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=237, total_tokens=255))
["auto top-up issue", "top-up activation problem", "enable auto top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there an auto top-up option?"

Keyphrases:
333it [05:29,  2.37s/it]
ChatCompletion(id='chatcmpl-9MyAvmUOupz7LpWpTI47BurqIEr1F', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top-up", "automatic reload", "recurring payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715261557, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["auto top-up", "automatic reload", "recurring payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "where is theft-top option?"

Keyphrases:
334it [05:31,  2.37s/it]
ChatCompletion(id='chatcmpl-9MyAxrTzthVDanxQH3BF2SPy0VSgV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["theft protection", "security options", "fraud prevention"]', role='assistant', function_call=None, tool_calls=None))], created=1715261559, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["theft protection", "security options", "fraud prevention"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there limits on auto top-up?"

Keyphrases:
335it [05:33,  2.13s/it]
ChatCompletion(id='chatcmpl-9MyAzEUdLefOc25EqcICZpCDBnTUv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top-up limits", "top-up restrictions", "maximum auto top-up amount"]', role='assistant', function_call=None, tool_calls=None))], created=1715261561, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=226, total_tokens=244))
["auto top-up limits", "top-up restrictions", "maximum auto top-up amount"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "can you assist me with the auto top up ?"

Keyphrases:
336it [05:35,  2.09s/it]
ChatCompletion(id='chatcmpl-9MyB1J9a8ZKXZOIK7B0yYJDE57WxH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top up assistance", "setup auto top up", "auto recharge help"]', role='assistant', function_call=None, tool_calls=None))], created=1715261563, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["auto top up assistance", "setup auto top up", "auto recharge help"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you have any limit on the auto top-up?"

Keyphrases:
337it [05:37,  2.15s/it]
ChatCompletion(id='chatcmpl-9MyB3Qxtn1ggv1aTAzezPQkmJp2yM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top-up limit", "top-up restrictions", "maximum auto top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715261565, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["auto top-up limit", "top-up restrictions", "maximum auto top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why are there limits on auto top-up?"

Keyphrases:
338it [05:39,  2.06s/it]
ChatCompletion(id='chatcmpl-9MyB5RuPsVn6OWGvN06TXNC3kf0jX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top-up limits", "top-up restrictions", "transaction limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715261567, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["auto top-up limits", "top-up restrictions", "transaction limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I top up automatically?"

Keyphrases:
339it [05:42,  2.31s/it]
ChatCompletion(id='chatcmpl-9MyB7YD4KpDPyh24g4LSFbvRmB7ep', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["automatic top-up", "recurring deposit", "set up auto top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715261569, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=17, prompt_tokens=225, total_tokens=242))
["automatic top-up", "recurring deposit", "set up auto top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I make sure I don't run out of money on my card while traveling?"

Keyphrases:
340it [05:45,  2.57s/it]
ChatCompletion(id='chatcmpl-9MyBACklgc6DZ55SPuGrIGcfnCswR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["travel funds management", "maintaining card balance", "avoiding card shortage"]', role='assistant', function_call=None, tool_calls=None))], created=1715261572, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=236, total_tokens=253))
["travel funds management", "maintaining card balance", "avoiding card shortage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What's the limit on automatic top-up?"

Keyphrases:
341it [05:46,  2.30s/it]
ChatCompletion(id='chatcmpl-9MyBDnsYFuD58IEbWsEwYq5X7oMNv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "automatic recharge limit", "maximum top-up amount"]', role='assistant', function_call=None, tool_calls=None))], created=1715261575, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["top-up limit", "automatic recharge limit", "maximum top-up amount"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I will be traveling, is there a way to auto top-up my card on certain days?"

Keyphrases:
342it [05:48,  1.98s/it]
ChatCompletion(id='chatcmpl-9MyBFc3YSzPv9FIXRYMWunmZ4eOqU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["travel top-up", "automatic reload", "scheduled top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715261577, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=238, total_tokens=252))
["travel top-up", "automatic reload", "scheduled top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is the auto top-up option?"

Keyphrases:
343it [05:49,  1.85s/it]
ChatCompletion(id='chatcmpl-9MyBGJT98WuqfgLZgfPIJ52lbJmYM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top-up", "enable auto top-up", "auto top-up settings"]', role='assistant', function_call=None, tool_calls=None))], created=1715261578, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["auto top-up", "enable auto top-up", "auto top-up settings"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I have a auto top-up when my account is short?"

Keyphrases:
344it [05:51,  1.80s/it]
ChatCompletion(id='chatcmpl-9MyBIXE7AwnMwApw78GwXHVTBLTSK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top-up", "automatic balance replenishment", "low balance top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715261580, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["auto top-up", "automatic balance replenishment", "low balance top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you have an auto top-up option?"

Keyphrases:
345it [05:52,  1.68s/it]
ChatCompletion(id='chatcmpl-9MyBJ2lmfKHaZrC9N817A0ya1u0Wk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top-up", "automatic reload", "recurring payment option"]', role='assistant', function_call=None, tool_calls=None))], created=1715261581, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["auto top-up", "automatic reload", "recurring payment option"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I space out how often money is transferred along my travels?"

Keyphrases:
346it [05:54,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyBLKYV17whA9idIHangKSQM1yqR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["schedule transfers", "periodic transfers", "automate transfers"]', role='assistant', function_call=None, tool_calls=None))], created=1715261583, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["schedule transfers", "periodic transfers", "automate transfers"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will it automatically top-up money if there isn't a lot left?"

Keyphrases:
347it [05:56,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyBNyVhUBL2d2Yu9pmt0dd5sa59a', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["automatic top-up", "low balance", "auto-reload"]', role='assistant', function_call=None, tool_calls=None))], created=1715261585, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["automatic top-up", "low balance", "auto-reload"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I have it add money automatically in certain intervals?"

Keyphrases:
348it [06:00,  2.51s/it]
ChatCompletion(id='chatcmpl-9MyBOnuIqhlq9Y7Ykgt8iE4zu4Sw2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["automatic deposits", "scheduled transfers", "recurring payments"]', role='assistant', function_call=None, tool_calls=None))], created=1715261586, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["automatic deposits", "scheduled transfers", "recurring payments"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I set up an automatic top-up for travel."

Keyphrases:
349it [06:03,  2.46s/it]
ChatCompletion(id='chatcmpl-9MyBTzBS8SGpLdsvbrM1L9xaNgtKK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["automatic top-up", "recurring payment setup", "travel funds automation"]', role='assistant', function_call=None, tool_calls=None))], created=1715261591, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["automatic top-up", "recurring payment setup", "travel funds automation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've tried looking for the auto-top up option on your website and I can't seem to find it. Can you help me?"

Keyphrases:
350it [06:04,  2.22s/it]
ChatCompletion(id='chatcmpl-9MyBV9XHNIEBx9k9eZh0c9Ksx3EVE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto-top up", "enable auto-top up", "find auto-top up option"]', role='assistant', function_call=None, tool_calls=None))], created=1715261593, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=245, total_tokens=263))
["auto-top up", "enable auto-top up", "find auto-top up option"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how do I top up my money automatically"

Keyphrases:
351it [06:06,  2.10s/it]
ChatCompletion(id='chatcmpl-9MyBXBMsPTOUqDxulACa9cCMA5hZm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["automatic top-up", "set up auto-reload", "enable automatic balance refill"]', role='assistant', function_call=None, tool_calls=None))], created=1715261595, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=227, total_tokens=245))
["automatic top-up", "set up auto-reload", "enable automatic balance refill"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I be topped up once I hit a certain balance?"

Keyphrases:
352it [06:08,  1.93s/it]
ChatCompletion(id='chatcmpl-9MyBYydcgeFUPHIpIg7wxsxSgoUaX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["automatic top-up", "balance threshold top-up", "auto-reload"]', role='assistant', function_call=None, tool_calls=None))], created=1715261596, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["automatic top-up", "balance threshold top-up", "auto-reload"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will it automatically top-up if there isn't much money left?"

Keyphrases:
353it [06:10,  2.04s/it]
ChatCompletion(id='chatcmpl-9MyBaYsuR1cdVjVuJgYJjYWME9xCM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["automatic top-up", "low balance", "recharge account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261598, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["automatic top-up", "low balance", "recharge account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there any way to Auto top-up?"

Keyphrases:
354it [06:12,  1.98s/it]
ChatCompletion(id='chatcmpl-9MyBcmPP8zRmREu9XqWLgYh3f4vkH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top-up", "automatic reload", "balance auto-replenishment"]', role='assistant', function_call=None, tool_calls=None))], created=1715261600, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["auto top-up", "automatic reload", "balance auto-replenishment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you explain where I can find the auto-top option?"

Keyphrases:
355it [06:14,  2.03s/it]
ChatCompletion(id='chatcmpl-9MyBfrEx29iR6N8lzETS813VyCQxx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto-top feature", "locate features", "navigation assistance"]', role='assistant', function_call=None, tool_calls=None))], created=1715261603, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["auto-top feature", "locate features", "navigation assistance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the auto top up function and where can I find that at?"

Keyphrases:
356it [06:16,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyBgUGBOGvyjGR9pZhTLIw9r7vJF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top up", "auto reload feature", "find auto top up settings"]', role='assistant', function_call=None, tool_calls=None))], created=1715261604, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=233, total_tokens=250))
["auto top up", "auto reload feature", "find auto top up settings"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a way to top-up automatically?"

Keyphrases:
357it [06:19,  2.35s/it]
ChatCompletion(id='chatcmpl-9MyBij579cklAd1NWRcmGWOEtsTfB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["automatic top-up", "recurring deposit", "scheduled top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715261606, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["automatic top-up", "recurring deposit", "scheduled top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a top-up feature, if there isn't a lot of money left?"

Keyphrases:
358it [06:22,  2.46s/it]
ChatCompletion(id='chatcmpl-9MyBlHsu1Txpfa8qg0yUgnQkrcMOK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up feature", "account reload", "balance refill"]', role='assistant', function_call=None, tool_calls=None))], created=1715261609, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=235, total_tokens=248))
["top-up feature", "account reload", "balance refill"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the highest limit for Auto Top?"

Keyphrases:
359it [06:24,  2.41s/it]
ChatCompletion(id='chatcmpl-9MyBoCS8OXBYMkFgMfjwHDyf2TDDY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto top-up limit", "maximum top-up", "top-up restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715261612, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["auto top-up limit", "maximum top-up", "top-up restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I enable auto-top up?"

Keyphrases:
360it [06:28,  2.84s/it]
ChatCompletion(id='chatcmpl-9MyBqklTnIpddmRsRAv6OeVg8bh7W', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["auto-top up", "enable automatic recharge", "set up auto-refill"]', role='assistant', function_call=None, tool_calls=None))], created=1715261614, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["auto-top up", "enable automatic recharge", "set up auto-refill"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've tried my card a bunch of times and it never worked."

Keyphrases:
361it [06:30,  2.53s/it]
ChatCompletion(id='chatcmpl-9MyBvA0lDxmJxEu3rp53n777ctm4C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "failed transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715261619, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["card malfunction", "card not working", "failed transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't get my card to work."

Keyphrases:
362it [06:33,  2.82s/it]
ChatCompletion(id='chatcmpl-9MyBy5kk0E2yEGlgrI5Ywl9NWwaQA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card issue", "card not working", "troubleshoot card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261622, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["card issue", "card not working", "troubleshoot card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card appears to be broken how can I fix it?"

Keyphrases:
363it [06:35,  2.55s/it]
ChatCompletion(id='chatcmpl-9MyBzuXmcylxIaIbiGkLwF4Kat8Gf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card repair", "broken card", "replace card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261623, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["card repair", "broken card", "replace card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I know why my card isn't working?"

Keyphrases:
364it [06:36,  2.16s/it]
ChatCompletion(id='chatcmpl-9MyC1x8jgohmHApdsBHDG8CxraKDh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card issue", "card not working", "troubleshoot card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261625, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["card issue", "card not working", "troubleshoot card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card broke."

Keyphrases:
365it [06:38,  1.97s/it]
ChatCompletion(id='chatcmpl-9MyC2rKaftOiGhwK6FDCgomUzK580', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["damaged card", "replace card", "card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261626, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=222, total_tokens=235))
["damaged card", "replace card", "card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card won't work."

Keyphrases:
366it [06:39,  1.78s/it]
ChatCompletion(id='chatcmpl-9MyC4lgkLKJg8azY8JsffbAV9IAch', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261628, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["card malfunction", "card not working", "payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my card not working?"

Keyphrases:
367it [06:41,  1.78s/it]
ChatCompletion(id='chatcmpl-9MyC5YMOGShaRWvWK0eYyQnfAL080', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "troubleshoot card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261629, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["card malfunction", "card not working", "troubleshoot card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you please identify the problem with my bank card?"

Keyphrases:
368it [06:42,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyC7Km0rdlJ0SuskTtiwdIWnuaXv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card issue", "bank card problem", "card malfunction"]', role='assistant', function_call=None, tool_calls=None))], created=1715261631, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["card issue", "bank card problem", "card malfunction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I unblock my card using the app?"

Keyphrases:
369it [06:44,  1.64s/it]
ChatCompletion(id='chatcmpl-9MyC9Rk16An4f54Tq3vQQFeofNEOb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unblock card", "app card management", "card unblocking process"]', role='assistant', function_call=None, tool_calls=None))], created=1715261633, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["unblock card", "app card management", "card unblocking process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card does not work"

Keyphrases:
370it [06:46,  1.71s/it]
ChatCompletion(id='chatcmpl-9MyCAnAnXm6NHZgfzK89C1riA5OrS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "card issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715261634, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["card malfunction", "card not working", "card issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I get my physical card to work?"

Keyphrases:
371it [06:47,  1.64s/it]
ChatCompletion(id='chatcmpl-9MyCCIx9QnKEFKEbuYaqrIq4MOApH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["activate card", "physical card activation", "card not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715261636, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["activate card", "physical card activation", "card not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can someone assist me by explaining why my card is not working?"

Keyphrases:
372it [06:49,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyCD0AAAOOmDINvYGWZs1y7AsBCE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card issue", "card not working", "technical support for card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261637, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["card issue", "card not working", "technical support for card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help me.  My card doesn't work."

Keyphrases:
373it [06:50,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyCFvAVoDi31kCA9bG8OAX7mI9Iw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "troubleshoot card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261639, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["card malfunction", "card not working", "troubleshoot card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can a card stop working?"

Keyphrases:
374it [06:53,  1.83s/it]
ChatCompletion(id='chatcmpl-9MyCHoXNg820FJ0IF2owSWARYV3TF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card issues", "non-working card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261641, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["card malfunction", "card issues", "non-working card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think my card is broken"

Keyphrases:
375it [06:54,  1.78s/it]
ChatCompletion(id='chatcmpl-9MyCJlNTtcJErpe9jBOQxNf5v5N9C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "broken card", "replace card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261643, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["card malfunction", "broken card", "replace card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why isn't my card working?"

Keyphrases:
376it [06:56,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyCLj6h31kNuMS1bgpVKY8csvDen', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card issue", "card not working", "payment problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715261645, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["card issue", "card not working", "payment problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card isn't working anymore."

Keyphrases:
377it [06:57,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyCMpGAX5UPefJESd736Xc7Qflja', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261646, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["card malfunction", "card not working", "card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card was declined today when eating and I need to know what's wrong."

Keyphrases:
378it [06:59,  1.72s/it]
ChatCompletion(id='chatcmpl-9MyCNuORJP4VtsA8Odd612xNNMm03', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "transaction issue", "payment failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715261647, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=234, total_tokens=246))
["card declined", "transaction issue", "payment failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card doesn't work."

Keyphrases:
379it [07:01,  1.74s/it]
ChatCompletion(id='chatcmpl-9MyCQKj4v0qjtORTY9JPA5BqIZ83L', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261650, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["card malfunction", "card not working", "card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I resolve a problem where my card won't go through at all?"

Keyphrases:
380it [07:02,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyCRRAvmjH4vleSchVTK2zw1x63Y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "transaction issue", "payment not processed"]', role='assistant', function_call=None, tool_calls=None))], created=1715261651, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["card declined", "transaction issue", "payment not processed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My actual card isn't working."

Keyphrases:
381it [07:03,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyCTSx3e592wq3rSryn3WkjsCXfD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "fix card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261653, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["card malfunction", "card not working", "fix card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is my card broken?"

Keyphrases:
382it [07:05,  1.48s/it]
ChatCompletion(id='chatcmpl-9MyCUUpVHZWnAILWuzv3KLH2BLuOV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card issue", "broken card", "card malfunction"]', role='assistant', function_call=None, tool_calls=None))], created=1715261654, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["card issue", "broken card", "card malfunction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I broke my card"

Keyphrases:
383it [07:07,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyCVUIUNL3UyfInp33VRlm4lA7bU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card damaged", "replace card", "broken card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261655, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["card damaged", "replace card", "broken card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card stopped working"

Keyphrases:
384it [07:10,  2.13s/it]
ChatCompletion(id='chatcmpl-9MyCX2t8ymE7dfRFrUtmg9sVQY0Wd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "card issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715261657, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["card malfunction", "card not working", "card issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is broke, what do I do?"

Keyphrases:
385it [07:12,  2.12s/it]
ChatCompletion(id='chatcmpl-9MyCa9PTtAo0Kdx3hlN9I3eKwhhhM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["damaged card", "replace card", "report broken card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261660, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["damaged card", "replace card", "report broken card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried using my card today and it's not working, can you help me?"

Keyphrases:
386it [07:15,  2.29s/it]
ChatCompletion(id='chatcmpl-9MyCdJS0QvbQCENaRUEe3PomgOabz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card not working", "card assistance", "card troubleshooting"]', role='assistant', function_call=None, tool_calls=None))], created=1715261663, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=235, total_tokens=248))
["card not working", "card assistance", "card troubleshooting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card stopped working when I use it"

Keyphrases:
387it [07:16,  2.02s/it]
ChatCompletion(id='chatcmpl-9MyCf9ciKSvqpRyp94A2Ys54ywKH1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261665, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["card malfunction", "card not working", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't use my card."

Keyphrases:
388it [07:18,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyChVWXnK0FQR4SHfksAqQlyrXnq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card issue", "unable to use card", "card not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715261667, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["card issue", "unable to use card", "card not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Need help with my card. It's not working."

Keyphrases:
389it [07:19,  1.65s/it]
ChatCompletion(id='chatcmpl-9MyCiC63WR9khv1tHoTLiY5Zgeu7B', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card issue", "card not working", "troubleshoot card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261668, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["card issue", "card not working", "troubleshoot card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I cannot use my card."

Keyphrases:
390it [07:21,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyCkQdDBeNmrcNpScBITeSWaBCKB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card not working", "card issue", "unable to use card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261670, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["card not working", "card issue", "unable to use card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The card I've got seems to be broken."

Keyphrases:
391it [07:22,  1.63s/it]
ChatCompletion(id='chatcmpl-9MyClpvCZ8sQKxXJQnmEegU06o1pp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card issue", "broken card", "replace card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261671, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["card issue", "broken card", "replace card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card isn't working"

Keyphrases:
392it [07:24,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyCmGBmrMK1Ac17UUCTE38tFMl0e', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "troubleshoot card issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715261672, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=224, total_tokens=240))
["card malfunction", "card not working", "troubleshoot card issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card suddenly quit working."

Keyphrases:
393it [07:26,  1.67s/it]
ChatCompletion(id='chatcmpl-9MyCoCDYQ5vWKUOkppxEA1C3kviek', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261674, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["card malfunction", "card not working", "card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have tried to use my card several times and it does not work."

Keyphrases:
394it [07:27,  1.49s/it]
ChatCompletion(id='chatcmpl-9MyCqQFlVm8bgGQilCMYnGiona41X', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "failed transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715261676, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["card malfunction", "card not working", "failed transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The card I have doesn't work."

Keyphrases:
395it [07:28,  1.34s/it]
ChatCompletion(id='chatcmpl-9MyCrdIKoEa76wgvGjpMmn86fXwrP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "broken card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261677, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card malfunction", "card not working", "broken card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card doesn't accept any transaction at all. What's wrong??"

Keyphrases:
396it [07:30,  1.52s/it]
ChatCompletion(id='chatcmpl-9MyCsUzg7u6cCxtQ3RFAcaI50OJit', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card transaction issue", "transaction failure", "card not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715261678, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["card transaction issue", "transaction failure", "card not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can i check if my card is working?"

Keyphrases:
397it [07:32,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyCuTI17rL1NxSWPgaTMdBUkYI14', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card functionality", "check card status", "card working"]', role='assistant', function_call=None, tool_calls=None))], created=1715261680, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["card functionality", "check card status", "card working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Nothing goes through on my card."

Keyphrases:
398it [07:33,  1.69s/it]
ChatCompletion(id='chatcmpl-9MyCwvme1oDAX1us6gXj7OohoCRbU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card issues", "transaction failure", "card declined"]', role='assistant', function_call=None, tool_calls=None))], created=1715261682, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["card issues", "transaction failure", "card declined"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I find out why my card won't work?"

Keyphrases:
399it [07:35,  1.71s/it]
ChatCompletion(id='chatcmpl-9MyCyfWgLdU4CJEPKDUgKagy5BkFA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card troubleshooting", "card not working", "resolve card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261684, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["card troubleshooting", "card not working", "resolve card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Could it be that I deactivated my card, its not working?"

Keyphrases:
400it [07:38,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyCzWEEfE7szRtG9t1ntPC88SK3i', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card deactivation", "inactive card", "card not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715261685, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["card deactivation", "inactive card", "card not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "May I exchange currencies with this?"

Keyphrases:
401it [07:40,  1.97s/it]
ChatCompletion(id='chatcmpl-9MyD2Bu70mBlfUZhOxHgmTDh9hheb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "foreign exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715261688, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["currency exchange", "exchange rates", "foreign exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Tell me how I can exchange between different currency."

Keyphrases:
402it [07:41,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyD4WTAIQTaYKOfMOaeEJaKEjC5J', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "foreign exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715261690, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["currency exchange", "exchange rates", "foreign exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I change from one currency to another?"

Keyphrases:
403it [07:42,  1.65s/it]
ChatCompletion(id='chatcmpl-9MyD5Ob8ktehhuB65yWa9hMMqxDrL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "convert currency", "forex services"]', role='assistant', function_call=None, tool_calls=None))], created=1715261691, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["currency exchange", "convert currency", "forex services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I change GBP to AUD?"

Keyphrases:
404it [07:44,  1.67s/it]
ChatCompletion(id='chatcmpl-9MyD7mu0X6y5ywc1oMVUest9TMXCC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "GBP to AUD", "foreign exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715261693, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["currency exchange", "GBP to AUD", "foreign exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will this app exchange currencies?"

Keyphrases:
405it [07:45,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyD8h3qAFlefIVNhOnKvdU6yt7Tp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "foreign currency transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715261694, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["currency exchange", "exchange rates", "foreign currency transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I convert currencies with the app?"

Keyphrases:
406it [07:46,  1.41s/it]
ChatCompletion(id='chatcmpl-9MyD9hoZE15zoc8r18mCAcDVCZ9U9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency conversion", "exchange rate", "convert money"]', role='assistant', function_call=None, tool_calls=None))], created=1715261695, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["currency conversion", "exchange rate", "convert money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How are currencies exchanged?"

Keyphrases:
407it [07:48,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyDBtIHC4AlRCD4rjJpBeiuqVdYi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "forex"]', role='assistant', function_call=None, tool_calls=None))], created=1715261697, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["currency exchange", "exchange rates", "forex"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I exchange currencies with this app?"

Keyphrases:
408it [07:50,  1.48s/it]
ChatCompletion(id='chatcmpl-9MyDD4P27XTdw0F12uH0j2FlA8YPt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "foreign currency transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715261699, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["currency exchange", "exchange rates", "foreign currency transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I make an exchange from one currency to another?"

Keyphrases:
409it [07:52,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyDEo1f9KcrU4Rr112FZMouLeaR6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "make currency exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715261700, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["currency exchange", "exchange rates", "make currency exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I interconvert between AUD and GBP?"

Keyphrases:
410it [07:55,  2.09s/it]
ChatCompletion(id='chatcmpl-9MyDHBRLkbw8NRjMcSUhKsnKNavWX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "AUD to GBP", "forex rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715261703, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["currency exchange", "AUD to GBP", "forex rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What all currencies can be exchanged?"

Keyphrases:
411it [07:56,  1.83s/it]
ChatCompletion(id='chatcmpl-9MyDJjB7XzFUnr2fx8WZklpeGx6A9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "available currencies", "foreign exchange options"]', role='assistant', function_call=None, tool_calls=None))], created=1715261705, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["currency exchange", "available currencies", "foreign exchange options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the best way to exchange currency between USD and GBP using your app?"

Keyphrases:
412it [07:57,  1.65s/it]
ChatCompletion(id='chatcmpl-9MyDKB1XmmUxuFR3vBkHW1hY3tVcS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "USD to GBP", "exchange rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715261706, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["currency exchange", "USD to GBP", "exchange rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I wanted to make a change from GBP to AUD what is the process?"

Keyphrases:
413it [07:59,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyDMZZOXPlJUiEMRdY11PtBEymUR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange process", "GBP to AUD"]', role='assistant', function_call=None, tool_calls=None))], created=1715261708, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["currency exchange", "exchange process", "GBP to AUD"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get some money exchanged?"

Keyphrases:
414it [08:00,  1.48s/it]
ChatCompletion(id='chatcmpl-9MyDN3EmxLAQt7LzuNr1YwUVwJgMG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "money exchange", "exchange rate"]', role='assistant', function_call=None, tool_calls=None))], created=1715261709, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["currency exchange", "money exchange", "exchange rate"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to change to another currency?"

Keyphrases:
415it [08:03,  2.03s/it]
ChatCompletion(id='chatcmpl-9MyDQlOfx6V3Z4s7ZcNu6JiRmqLHq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "change currency", "currency swap"]', role='assistant', function_call=None, tool_calls=None))], created=1715261712, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["currency exchange", "change currency", "currency swap"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I exchange my GBP to AUD?"

Keyphrases:
416it [08:04,  1.78s/it]
ChatCompletion(id='chatcmpl-9MyDSskZ8JOvQhQ0ezhGIFKTRh5Yi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "GBP to AUD"]', role='assistant', function_call=None, tool_calls=None))], created=1715261714, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["currency exchange", "exchange rates", "GBP to AUD"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How would I use my money in a different country?"

Keyphrases:
417it [08:06,  1.58s/it]
ChatCompletion(id='chatcmpl-9MyDTFEWpXTTPy2WsAjMa50uds7YH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international spending", "using bank account abroad", "foreign transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715261715, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["international spending", "using bank account abroad", "foreign transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I receive foreign currencies, am I able to exchange them on the app?"

Keyphrases:
418it [08:07,  1.50s/it]
ChatCompletion(id='chatcmpl-9MyDUrVs0PB9Ddq5TO9zOAv7cghUx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "foreign currency", "exchange rate"]', role='assistant', function_call=None, tool_calls=None))], created=1715261716, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=234, total_tokens=246))
["currency exchange", "foreign currency", "exchange rate"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I change to another currency?"

Keyphrases:
419it [08:08,  1.50s/it]
ChatCompletion(id='chatcmpl-9MyDVe4v5S6EjkCGadtkNcEnfdpxJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "change currency", "swap currency"]', role='assistant', function_call=None, tool_calls=None))], created=1715261717, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["currency exchange", "change currency", "swap currency"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need AUD not GBP, how do I change it?"

Keyphrases:
420it [08:10,  1.39s/it]
ChatCompletion(id='chatcmpl-9MyDXb8OUaEXAE5auDNRF5jECb9zX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "change currency", "modify transaction currency"]', role='assistant', function_call=None, tool_calls=None))], created=1715261719, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["currency exchange", "change currency", "modify transaction currency"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the best way to exchange currency?"

Keyphrases:
421it [08:11,  1.38s/it]
ChatCompletion(id='chatcmpl-9MyDYerD11DJ1xuZYer9NSDLuVYAq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "best exchange methods", "foreign currency exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715261720, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["currency exchange", "best exchange methods", "foreign currency exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I need GBP instead of AUD what do I do?"

Keyphrases:
422it [08:12,  1.34s/it]
ChatCompletion(id='chatcmpl-9MyDZrXrDUpTIVVfiIGeHx22Wqg68', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "switch currency", "GBP instead of AUD"]', role='assistant', function_call=None, tool_calls=None))], created=1715261721, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["currency exchange", "switch currency", "GBP instead of AUD"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was wondering whether exchanging currencies can be done on this app."

Keyphrases:
423it [08:13,  1.34s/it]
ChatCompletion(id='chatcmpl-9MyDa2qC5e2jWk0vHcd1LRz2EE7uB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rate", "forex services"]', role='assistant', function_call=None, tool_calls=None))], created=1715261722, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["currency exchange", "exchange rate", "forex services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I might need AUD instead of GBP, how to change?"

Keyphrases:
424it [08:15,  1.33s/it]
ChatCompletion(id='chatcmpl-9MyDcNSSmUJUEdHpVRK664dQBCE6r', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "change currency", "switch currency"]', role='assistant', function_call=None, tool_calls=None))], created=1715261724, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["currency exchange", "change currency", "switch currency"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I go through the process of currency exchange?"

Keyphrases:
425it [08:16,  1.30s/it]
ChatCompletion(id='chatcmpl-9MyDd123bcIS7YF9Z6rP3Nz02oCBf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange process", "exchange rates", "forex transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715261725, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["currency exchange process", "exchange rates", "forex transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Change currency"

Keyphrases:
426it [08:17,  1.27s/it]
ChatCompletion(id='chatcmpl-9MyDez3ZkWu8WVupPl5htqrRR9W8t', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "change currency setting", "update currency preference"]', role='assistant', function_call=None, tool_calls=None))], created=1715261726, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=221, total_tokens=235))
["currency exchange", "change currency setting", "update currency preference"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can am I able to exchange currencies?"

Keyphrases:
427it [08:19,  1.49s/it]
ChatCompletion(id='chatcmpl-9MyDfMoWJzUvomv1N65vAf2p2Il3C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "foreign exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715261727, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["currency exchange", "exchange rates", "foreign exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I go to change GBP?"

Keyphrases:
428it [08:21,  1.51s/it]
ChatCompletion(id='chatcmpl-9MyDhUu1Fm6DD44YA0SYybePuQRCe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "GBP exchange location", "foreign exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715261729, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["currency exchange", "GBP exchange location", "foreign exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What currency's can i exchange for?"

Keyphrases:
429it [08:23,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyDjYbm3jcAxPL4HYCepoHGaTw8b', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "foreign exchange options", "available currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715261731, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["currency exchange", "foreign exchange options", "available currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What currencies will this app exchange?"

Keyphrases:
430it [08:24,  1.53s/it]
ChatCompletion(id='chatcmpl-9MyDlWfR7CeZCjMqtzhARsrLn30v1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "available currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715261733, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["currency exchange", "exchange rates", "available currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can this app help me exchange currencies?"

Keyphrases:
431it [08:25,  1.38s/it]
ChatCompletion(id='chatcmpl-9MyDmdh3daVCJRErzv0CPtBAvrz51', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rate", "money conversion"]', role='assistant', function_call=None, tool_calls=None))], created=1715261734, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["currency exchange", "exchange rate", "money conversion"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to exchange some currency."

Keyphrases:
432it [08:26,  1.35s/it]
ChatCompletion(id='chatcmpl-9MyDnKaGEI3gQz6LyewsXIgX6LbNr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "foreign exchange", "exchange rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715261735, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["currency exchange", "foreign exchange", "exchange rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I exchange between GBP and USD on the app?"

Keyphrases:
433it [08:27,  1.28s/it]
ChatCompletion(id='chatcmpl-9MyDoFwb5ZSaPmzPIwbGkpZwybaef', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "GBP to USD", "exchange rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715261736, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["currency exchange", "GBP to USD", "exchange rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there currency exchange on this app?"

Keyphrases:
434it [08:29,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyDqKg1uYjSbMokr8po5Av6qmhhz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rate", "foreign currency"]', role='assistant', function_call=None, tool_calls=None))], created=1715261738, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["currency exchange", "exchange rate", "foreign currency"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I change my currency from USD to EUR?"

Keyphrases:
435it [08:30,  1.32s/it]
ChatCompletion(id='chatcmpl-9MyDr9HQaTGsWezTJIuCiq1c2Qyum', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "change currency", "USD to EUR"]', role='assistant', function_call=None, tool_calls=None))], created=1715261739, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["currency exchange", "change currency", "USD to EUR"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think I want AUD and not GBP, can you help?"

Keyphrases:
436it [08:32,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyDtjsG18uyTe1eAhy3mmnC4VFRs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "currency correction", "change currency order"]', role='assistant', function_call=None, tool_calls=None))], created=1715261741, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["currency exchange", "currency correction", "change currency order"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I exchange currency?"

Keyphrases:
437it [08:33,  1.35s/it]
ChatCompletion(id='chatcmpl-9MyDuaD4PwgIt4vib0PYpBiIekVEv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "foreign currency"]', role='assistant', function_call=None, tool_calls=None))], created=1715261742, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["currency exchange", "exchange rates", "foreign currency"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use this app to change dollars into euros?"

Keyphrases:
438it [08:35,  1.38s/it]
ChatCompletion(id='chatcmpl-9MyDwcaa8dnj9nmuJFpTZXlU8GWTU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "convert currency", "money conversion"]', role='assistant', function_call=None, tool_calls=None))], created=1715261744, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["currency exchange", "convert currency", "money conversion"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I exchange currencies with my account?"

Keyphrases:
439it [08:36,  1.33s/it]
ChatCompletion(id='chatcmpl-9MyDxVZ3RKCAI1FtbXDhHgyzGRJHU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "foreign exchange", "exchange rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715261745, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["currency exchange", "foreign exchange", "exchange rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to exchange currencies"

Keyphrases:
440it [08:37,  1.32s/it]
ChatCompletion(id='chatcmpl-9MyDyOxEc0tfTozITTutqKmyU6j7Z', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "foreign currency transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715261746, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["currency exchange", "exchange rates", "foreign currency transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My entire gym bag, including my wallet, was stolen out of my locker today. Everything in my wallet is gone - how do I block the card to make it can't be used?"

Keyphrases:
441it [08:38,  1.30s/it]
ChatCompletion(id='chatcmpl-9MyDzIyxoEonj6lNTYQITguFH2184', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["block card", "stolen card", "prevent unauthorized use"]', role='assistant', function_call=None, tool_calls=None))], created=1715261747, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=256, total_tokens=270))
["block card", "stolen card", "prevent unauthorized use"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't find my card and think it may have been stolen."

Keyphrases:
442it [08:40,  1.26s/it]
ChatCompletion(id='chatcmpl-9MyE1HW291iCsGTfoU4JMsPEfqFQI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost card", "stolen card", "card recovery"]', role='assistant', function_call=None, tool_calls=None))], created=1715261749, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["lost card", "stolen card", "card recovery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone stole my card. I need to report it stolen. I made a police report already, but how do I report it with you?"

Keyphrases:
443it [08:43,  2.06s/it]
ChatCompletion(id='chatcmpl-9MyE2RAjWR27Mazvr4YjIgcZMPhTK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["report stolen card", "card theft", "police report for stolen card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261750, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=17, prompt_tokens=246, total_tokens=263))
["report stolen card", "card theft", "police report for stolen card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I cant find my card, it's gone."

Keyphrases:
444it [08:45,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyE6gmPcdORTSf0YHXBBbLGbqzSf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing card", "lost card", "card not found"]', role='assistant', function_call=None, tool_calls=None))], created=1715261754, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["missing card", "lost card", "card not found"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is lost! What can I do?"

Keyphrases:
445it [08:46,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyE7R3Kc18UVo7PNwXKe3MkXRCqc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost card", "card replacement", "report lost card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261755, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["lost card", "card replacement", "report lost card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I lost my card"

Keyphrases:
446it [08:47,  1.53s/it]
ChatCompletion(id='chatcmpl-9MyE8XL3RFf91fVov1Wtnkt3kyARO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost card", "report lost card", "card replacement"]', role='assistant', function_call=None, tool_calls=None))], created=1715261756, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["lost card", "report lost card", "card replacement"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Oh no!  I lost my card!  Help!"

Keyphrases:
447it [08:48,  1.44s/it]
ChatCompletion(id='chatcmpl-9MyE9GxYOTWHRaNdpqdlr6EX2ux1o', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost card", "card replacement", "report lost card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261757, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["lost card", "card replacement", "report lost card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I believe my card has been stolen, what can I do about this situation? It's urgent."

Keyphrases:
448it [08:51,  1.89s/it]
ChatCompletion(id='chatcmpl-9MyEBqUitWRJQyHRbqQQ4TjX1FI4A', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen card", "report theft", "urgent card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261759, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=238, total_tokens=252))
["stolen card", "report theft", "urgent card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help! Someone stole my card!"

Keyphrases:
449it [08:53,  1.69s/it]
ChatCompletion(id='chatcmpl-9MyEEIR0SgetzK5jrkI1Xpw7mW5Q1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen card", "card theft", "block card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261762, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["stolen card", "card theft", "block card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help.  I have a stolen card!"

Keyphrases:
450it [08:54,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyEFlAlNmGfzm1HEYVPrgj1aGoHJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen card", "report theft", "block card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261763, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["stolen card", "report theft", "block card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "card is lost, please help"

Keyphrases:
451it [08:56,  1.56s/it]
ChatCompletion(id='chatcmpl-9MyEH1pYLmFlfrtgMgyoDyPnLpfIj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost card", "report lost card", "card assistance"]', role='assistant', function_call=None, tool_calls=None))], created=1715261765, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["lost card", "report lost card", "card assistance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I report my card stolen?"

Keyphrases:
452it [08:58,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyEIUsjRENjv82s24XHQKbUWftpp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["report stolen card", "stolen card", "fraudulent activity"]', role='assistant', function_call=None, tool_calls=None))], created=1715261766, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["report stolen card", "stolen card", "fraudulent activity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is gone I think it was stolen"

Keyphrases:
453it [08:59,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyEK4K2PxsTnwLIJEZRfC5E6OtCl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost card", "stolen card", "card replacement"]', role='assistant', function_call=None, tool_calls=None))], created=1715261768, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["lost card", "stolen card", "card replacement"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is a copy of the police report necessary for completing the report process?"

Keyphrases:
454it [09:01,  1.69s/it]
ChatCompletion(id='chatcmpl-9MyEM5Zy4M6Ge7PuH721uHn80lyRH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["police report requirement", "documentation for report", "report completion requirements"]', role='assistant', function_call=None, tool_calls=None))], created=1715261770, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["police report requirement", "documentation for report", "report completion requirements"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I lost my wallet today with all my credit cards. Will you please block the card and send a replacement?"

Keyphrases:
455it [09:02,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyEN7hxzl4O6Ghzk3REFhPkzcnjM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card block", "lost card", "replace card", "emergency card replacement"]', role='assistant', function_call=None, tool_calls=None))], created=1715261771, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=240, total_tokens=257))
["card block", "lost card", "replace card", "emergency card replacement"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I deal with a stolen card?"

Keyphrases:
456it [09:04,  1.58s/it]
ChatCompletion(id='chatcmpl-9MyEPMfNwd28aOOItc3rYkcUxncTi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["report stolen card", "stolen card actions", "block stolen card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261773, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["report stolen card", "stolen card actions", "block stolen card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you freeze my card it was stolen"

Keyphrases:
457it [09:05,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyEQP069EOZiYBLMDbtooqyTRP5O', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["freeze card", "stolen card", "card security"]', role='assistant', function_call=None, tool_calls=None))], created=1715261774, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["freeze card", "stolen card", "card security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help!  I can't find my card."

Keyphrases:
458it [09:06,  1.40s/it]
ChatCompletion(id='chatcmpl-9MyER6EjvRQKpZr0kc0xvADVsuHRX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing card", "lost card", "card not found"]', role='assistant', function_call=None, tool_calls=None))], created=1715261775, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["missing card", "lost card", "card not found"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What should I do if I lost my card?"

Keyphrases:
459it [09:08,  1.54s/it]
ChatCompletion(id='chatcmpl-9MyETf1Ofg60vcI0YplIGqbKAMOIY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost card", "report lost card", "card replacement"]', role='assistant', function_call=None, tool_calls=None))], created=1715261777, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["lost card", "report lost card", "card replacement"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need help with a lost card"

Keyphrases:
460it [09:12,  2.29s/it]
ChatCompletion(id='chatcmpl-9MyEWMcNBqmYJAbFPN7RLolfvDfPd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost card", "card assistance", "report lost card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261780, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["lost card", "card assistance", "report lost card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think my card was stolen."

Keyphrases:
461it [09:15,  2.40s/it]
ChatCompletion(id='chatcmpl-9MyEZHuHbtek1ACbCxlvkzlmUe3OV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card stolen", "report stolen card", "lost card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261783, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["card stolen", "report stolen card", "lost card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone stole my wallet earlier today, not sure exactly when, probably on Piccadilly circus. Can you check if there were any attempts to use the card and obviously block it?"

Keyphrases:
462it [09:16,  2.04s/it]
ChatCompletion(id='chatcmpl-9MyEbngSKRIxTZFMfIlw9j9WRedPz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card security", "block card", "unauthorized card usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715261785, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=254, total_tokens=268))
["card security", "block card", "unauthorized card usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think I lost my card . I dont know how long it has been missing. Can you see if maybe someone else has been using it?"

Keyphrases:
463it [09:17,  1.77s/it]
ChatCompletion(id='chatcmpl-9MyEcnESKdpblK7SKrcAiFXzroYUY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost card", "card misuse", "unauthorized transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715261786, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=247, total_tokens=260))
["lost card", "card misuse", "unauthorized transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I freeze a stolen card?"

Keyphrases:
464it [09:19,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyEekkvGZ4RhyVDdBIJSEJFZnt4T', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["freeze card", "stolen card", "block card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261788, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["freeze card", "stolen card", "block card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What should I do if my card is missing?"

Keyphrases:
465it [09:20,  1.51s/it]
ChatCompletion(id='chatcmpl-9MyEfm0DetdOtivk1wrBI7FqWwWoC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing card", "report lost card", "card replacement"]', role='assistant', function_call=None, tool_calls=None))], created=1715261789, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["missing card", "report lost card", "card replacement"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My bags were stolen. I need a new card but need to cancel the stolen one."

Keyphrases:
466it [09:21,  1.41s/it]
ChatCompletion(id='chatcmpl-9MyEgv5eG4YjIvj1Y1Vp4uiiRBQuH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel stolen card", "issue new card", "report stolen card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261790, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["cancel stolen card", "issue new card", "report stolen card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Somehow I am missing my card.  What should I do?"

Keyphrases:
467it [09:22,  1.41s/it]
ChatCompletion(id='chatcmpl-9MyEhGSVA7APIQ3sVPGGNEV5QxP98', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing card", "lost card assistance", "report missing card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261791, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["missing card", "lost card assistance", "report missing card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card was taken from me"

Keyphrases:
468it [09:25,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyEjz2NhXGmLqR85500FNKq8e07P', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen card", "card theft", "report stolen card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261793, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["stolen card", "card theft", "report stolen card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card got lost."

Keyphrases:
469it [09:26,  1.58s/it]
ChatCompletion(id='chatcmpl-9MyElmZmdiYUeuXG4Un1SD9sc3KNv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost card", "report card lost", "card replacement"]', role='assistant', function_call=None, tool_calls=None))], created=1715261795, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["lost card", "report card lost", "card replacement"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Some idiot stole my card."

Keyphrases:
470it [09:28,  1.53s/it]
ChatCompletion(id='chatcmpl-9MyEmJK96hhWCm91N9jLIxayNCkvs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen card", "card theft", "report stolen card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261796, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["stolen card", "card theft", "report stolen card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I report my card lost or stolen?"

Keyphrases:
471it [09:29,  1.46s/it]
ChatCompletion(id='chatcmpl-9MyEol7AfdxhalMGlnZkaGTwoPGyW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["report lost card", "report stolen card", "card security"]', role='assistant', function_call=None, tool_calls=None))], created=1715261798, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["report lost card", "report stolen card", "card security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is lost! What do I do now?"

Keyphrases:
472it [09:30,  1.48s/it]
ChatCompletion(id='chatcmpl-9MyEpKhkxRFgD6vWCbLWAsmRbODhe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost card", "report lost card", "card replacement"]', role='assistant', function_call=None, tool_calls=None))], created=1715261799, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["lost card", "report lost card", "card replacement"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm in Spain and my stuff has been stolen. My card was with it and I need a new one shipped and the old one frozen."

Keyphrases:
473it [09:32,  1.59s/it]
ChatCompletion(id='chatcmpl-9MyEr9d2wGqvXDhp0TdsVSfPSe1is', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen card", "freeze card", "card replacement", "emergency card request"]', role='assistant', function_call=None, tool_calls=None))], created=1715261801, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=247, total_tokens=265))
["stolen card", "freeze card", "card replacement", "emergency card request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I believe my credit card was stolen."

Keyphrases:
474it [09:33,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyEsFXf9zsCBoCgWMqoydBM9qN4v', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen card", "credit card theft", "report stolen card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261802, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["stolen card", "credit card theft", "report stolen card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I report a stolen card?"

Keyphrases:
475it [09:35,  1.42s/it]
ChatCompletion(id='chatcmpl-9MyEuQBOmjR1VcJOqMSI0j4deUz4V', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["report stolen card", "lost card", "card security"]', role='assistant', function_call=None, tool_calls=None))], created=1715261804, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["report stolen card", "lost card", "card security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Somebody has stolen my card, I need help please."

Keyphrases:
476it [09:37,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyEv1DZS63IrGdog0blVwmpxKriU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen card", "emergency report", "card theft"]', role='assistant', function_call=None, tool_calls=None))], created=1715261805, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["stolen card", "emergency report", "card theft"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I cannot find my credit card."

Keyphrases:
477it [09:38,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyEyRrV463c86AqR4mW3ComRS2ud', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing credit card", "credit card not found", "locate credit card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261808, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["missing credit card", "credit card not found", "locate credit card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are you able to locate my card?"

Keyphrases:
478it [09:40,  1.54s/it]
ChatCompletion(id='chatcmpl-9MyEzrvMcjhXpCXs4NZ5BgYfA2BSj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card location", "find card", "card whereabouts"]', role='assistant', function_call=None, tool_calls=None))], created=1715261809, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["card location", "find card", "card whereabouts"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card got stolen!"

Keyphrases:
479it [09:41,  1.50s/it]
ChatCompletion(id='chatcmpl-9MyF0ez54W8Wjqi1snk45AW3V4Zpt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["report stolen card", "card theft", "lost card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261810, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["report stolen card", "card theft", "lost card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help me please!  My card was stolen!"

Keyphrases:
480it [09:42,  1.40s/it]
ChatCompletion(id='chatcmpl-9MyF2hAfzucnsxLWpnzAyTK8dDXuX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen card", "report stolen card", "card theft assistance"]', role='assistant', function_call=None, tool_calls=None))], created=1715261812, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["stolen card", "report stolen card", "card theft assistance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how old do i need to be to get an account for myself"

Keyphrases:
481it [09:44,  1.43s/it]
ChatCompletion(id='chatcmpl-9MyF353t3CggLwuNW0ZroTPB0LxXa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account eligibility", "minimum age requirement", "age requirement for account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261813, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["account eligibility", "minimum age requirement", "age requirement for account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How young can I be to open my own account?"

Keyphrases:
482it [09:45,  1.40s/it]
ChatCompletion(id='chatcmpl-9MyF4dX2zMCD3llr3BcW8ZVN2ZrmR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["minimum age requirement", "open account age limit", "youth account eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715261814, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["minimum age requirement", "open account age limit", "youth account eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How old do I have to be?"

Keyphrases:
483it [09:47,  1.50s/it]
ChatCompletion(id='chatcmpl-9MyF6uefdFABGlCKQqcQB7tjYEbLP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["age requirement", "account eligibility", "minimum age policy"]', role='assistant', function_call=None, tool_calls=None))], created=1715261816, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["age requirement", "account eligibility", "minimum age policy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I open an account for a child?"

Keyphrases:
484it [09:49,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyF7RbqsUGd0PTeUab5wWzNZWn6v', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["child account", "minor account opening", "youth banking"]', role='assistant', function_call=None, tool_calls=None))], created=1715261817, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["child account", "minor account opening", "youth banking"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How old do we have to be?"

Keyphrases:
485it [09:51,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyFACvZknVD1m7i4iugiVRm9pWLw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["age requirement", "account eligibility", "minimum age policy"]', role='assistant', function_call=None, tool_calls=None))], created=1715261820, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["age requirement", "account eligibility", "minimum age policy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I go about setting up an account for my daughter?"

Keyphrases:
486it [09:52,  1.51s/it]
ChatCompletion(id='chatcmpl-9MyFBaursxUzZKgIlx0897aLKFzkp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account setup", "minor account", "additional account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261821, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["account setup", "minor account", "additional account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there an age minimum?"

Keyphrases:
487it [09:53,  1.46s/it]
ChatCompletion(id='chatcmpl-9MyFC0akxvyzAOEcyXkYdjYPuF84Y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["age requirement", "minimum age policy", "account eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715261822, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["age requirement", "minimum age policy", "account eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the youngest age in order to have an account?"

Keyphrases:
488it [09:55,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyFEzl2PzKK7ZpbCAf9HGaCh3vUu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account eligibility", "minimum age requirement", "opening account age limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715261824, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["account eligibility", "minimum age requirement", "opening account age limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What age do I have to be?"

Keyphrases:
489it [10:00,  2.45s/it]
ChatCompletion(id='chatcmpl-9MyFG9YMTYebBC86zBNoB9iyStH6f', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["age requirement", "account eligibility", "minimum age"]', role='assistant', function_call=None, tool_calls=None))], created=1715261826, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["age requirement", "account eligibility", "minimum age"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can my daughter open an account?"

Keyphrases:
490it [10:06,  3.68s/it]
ChatCompletion(id='chatcmpl-9MyFK8AAZUzYahBAbEVyMcfIpXD76', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account eligibility", "minor account opening", "dependent banking"]', role='assistant', function_call=None, tool_calls=None))], created=1715261830, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["account eligibility", "minor account opening", "dependent banking"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the minimum age to open an account?"

Keyphrases:
491it [10:10,  3.82s/it]
ChatCompletion(id='chatcmpl-9MyFRmamO9XRUezHDQQa32I0fnEEx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account eligibility", "minimum age requirement", "open account age limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715261837, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["account eligibility", "minimum age requirement", "open account age limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the minimum age?"

Keyphrases:
492it [10:15,  4.08s/it]
ChatCompletion(id='chatcmpl-9MyFWOy0XSs8lHfUdf48wjuj4m7fL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["minimum age requirement", "age eligibility", "account age restriction"]', role='assistant', function_call=None, tool_calls=None))], created=1715261842, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["minimum age requirement", "age eligibility", "account age restriction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am only 17. Can I make an account?"

Keyphrases:
493it [10:19,  3.95s/it]
ChatCompletion(id='chatcmpl-9MyFZUoRWNrN2OoqZZeQ8egYFmMUa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["age requirement", "account eligibility", "minor account opening"]', role='assistant', function_call=None, tool_calls=None))], created=1715261845, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["age requirement", "account eligibility", "minor account opening"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Could I open an account for my children?"

Keyphrases:
494it [10:21,  3.34s/it]
ChatCompletion(id='chatcmpl-9MyFd49Rkv0gVa2fmYZ333iWQi42T', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["open account", "child account", "minor account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261849, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["open account", "child account", "minor account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the age to open an account?"

Keyphrases:
495it [10:22,  2.86s/it]
ChatCompletion(id='chatcmpl-9MyFfgJex00EyqP43tQItD3IJSgSi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account eligibility", "minimum age requirement", "opening bank account age"]', role='assistant', function_call=None, tool_calls=None))], created=1715261851, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["account eligibility", "minimum age requirement", "opening bank account age"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I open up an account for my child?"

Keyphrases:
496it [10:25,  2.69s/it]
ChatCompletion(id='chatcmpl-9MyFhaQd6xVa2xpY6jlTcRfJPEj0w', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["child account creation", "open minor account", "youth account setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715261853, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["child account creation", "open minor account", "youth account setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I open a bank account for my newborn baby?"

Keyphrases:
497it [10:27,  2.51s/it]
ChatCompletion(id='chatcmpl-9MyFjoKsGMySg9FxiYLynr2azp7fx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["open bank account", "minor account", "newborn bank account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261855, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["open bank account", "minor account", "newborn bank account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How old do I have to be to open an account?"

Keyphrases:
498it [10:29,  2.57s/it]
ChatCompletion(id='chatcmpl-9MyFmAR8y4kLo2gjNyq75tGArdHsW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account eligibility", "minimum age requirement", "open account age"]', role='assistant', function_call=None, tool_calls=None))], created=1715261858, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["account eligibility", "minimum age requirement", "open account age"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you offer services for children to have money saving experience?"

Keyphrases:
499it [10:32,  2.45s/it]
ChatCompletion(id='chatcmpl-9MyFoYgKBP38d6ofw4KFl85czYLic', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["children\'s banking", "youth savings accounts", "kids money management"]', role='assistant', function_call=None, tool_calls=None))], created=1715261860, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["children's banking", "youth savings accounts", "kids money management"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If my kids wanted to use your service how old would they have to be?"

Keyphrases:
500it [10:34,  2.45s/it]
ChatCompletion(id='chatcmpl-9MyFqLhEmxf4Jg4Yi2hB73k4IbWVZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["age requirement", "service eligibility", "minor account policies"]', role='assistant', function_call=None, tool_calls=None))], created=1715261862, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["age requirement", "service eligibility", "minor account policies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can my 19 year old daughter open a savings account at the bank?"

Keyphrases:
501it [10:36,  2.20s/it]
ChatCompletion(id='chatcmpl-9MyFsEWeQd4GoeDy6Q9FwYJ6JKj2F', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["open savings account", "youth banking", "age eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715261864, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["open savings account", "youth banking", "age eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How old do you have to be to get an account?"

Keyphrases:
502it [10:37,  1.95s/it]
ChatCompletion(id='chatcmpl-9MyFubASc6QwF3zwIGj7neB5N3Apz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account eligibility", "minimum age requirement", "age requirement for account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261866, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["account eligibility", "minimum age requirement", "age requirement for account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What's the minimum age for opening an account?"

Keyphrases:
503it [10:38,  1.80s/it]
ChatCompletion(id='chatcmpl-9MyFv4wocO8rAsg1t6uvBovBnpOfQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account eligibility", "minimum age requirement", "opening account age criteria"]', role='assistant', function_call=None, tool_calls=None))], created=1715261867, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["account eligibility", "minimum age requirement", "opening account age criteria"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like an account for my children, how do I go about doing this?"

Keyphrases:
504it [10:41,  1.94s/it]
ChatCompletion(id='chatcmpl-9MyFxXKPO48WUIJfR4OnU8UfAr6kf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["children\'s account setup", "minor account", "opening account for minors"]', role='assistant', function_call=None, tool_calls=None))], created=1715261869, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=235, total_tokens=251))
["children's account setup", "minor account", "opening account for minors"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can my children have their own account?"

Keyphrases:
505it [10:45,  2.65s/it]
ChatCompletion(id='chatcmpl-9MyFzYBeqO3AeYKZINZN5Z3HXJE0p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["child account", "minor banking account", "family banking options"]', role='assistant', function_call=None, tool_calls=None))], created=1715261871, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["child account", "minor banking account", "family banking options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to open an account for my children?"

Keyphrases:
506it [10:47,  2.33s/it]
ChatCompletion(id='chatcmpl-9MyG3xTBWKnAFnSk6PAJ07ZUFpQ6S', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["open account for minors", "children\'s bank account", "youth account setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715261875, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=229, total_tokens=247))
["open account for minors", "children's bank account", "youth account setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do my kids have to be a certain age to use this service?"

Keyphrases:
507it [10:48,  2.07s/it]
ChatCompletion(id='chatcmpl-9MyG5DZqMOQ7aGeIuFhWivKDe93bY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["age requirement", "service eligibility", "children\'s account eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715261877, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["age requirement", "service eligibility", "children's account eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How old do you have to be to be able to open an account?"

Keyphrases:
508it [10:50,  2.01s/it]
ChatCompletion(id='chatcmpl-9MyG7GxxqznPJAr5O1halckjE6f5y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account eligibility", "minimum age requirement", "open account age restriction"]', role='assistant', function_call=None, tool_calls=None))], created=1715261879, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["account eligibility", "minimum age requirement", "open account age restriction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there an age limit?"

Keyphrases:
509it [10:52,  1.93s/it]
ChatCompletion(id='chatcmpl-9MyG8nZaYIBzint4gOyPRPIB49XzT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["age requirement", "age restriction", "account eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715261880, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["age requirement", "age restriction", "account eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the age requirements for opening an account?"

Keyphrases:
510it [10:54,  2.11s/it]
ChatCompletion(id='chatcmpl-9MyGAdqCxBvRguoRx3Q7VBYK25Nmv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account opening eligibility", "age requirement", "minimum age"]', role='assistant', function_call=None, tool_calls=None))], created=1715261882, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["account opening eligibility", "age requirement", "minimum age"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "will i be able to open an account for my daughter"

Keyphrases:
511it [10:56,  1.87s/it]
ChatCompletion(id='chatcmpl-9MyGCLmZexjFMoxsLinkLZ1ssl21J', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["open account", "account for family", "minor bank account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261884, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["open account", "account for family", "minor bank account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How old do I need to be to open an account?"

Keyphrases:
512it [10:57,  1.83s/it]
ChatCompletion(id='chatcmpl-9MyGEuoWNH4FD7M7y9xlx6Tv66CIs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account eligibility", "minimum age requirement", "age requirement for bank account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261886, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["account eligibility", "minimum age requirement", "age requirement for bank account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What age can sign up for services?"

Keyphrases:
513it [10:59,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyGF5Cyqi3ObKZYciTYbExMh3vK2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["age requirement", "sign up eligibility", "minimum age for account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261887, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["age requirement", "sign up eligibility", "minimum age for account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How old do my kids have to be to use your service?"

Keyphrases:
514it [11:03,  2.37s/it]
ChatCompletion(id='chatcmpl-9MyGHcZaCV8M2kgol2jNQP6dmBtp0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["age requirement", "children eligibility", "service age policy"]', role='assistant', function_call=None, tool_calls=None))], created=1715261889, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["age requirement", "children eligibility", "service age policy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What age do my kids need to be to use your service?"

Keyphrases:
515it [11:04,  2.11s/it]
ChatCompletion(id='chatcmpl-9MyGLe22pcYQtC27wsyxtjNBqFCL1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["child eligibility", "age requirement", "service age policy"]', role='assistant', function_call=None, tool_calls=None))], created=1715261893, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["child eligibility", "age requirement", "service age policy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How old do my children need to be to open an account?"

Keyphrases:
516it [11:06,  2.02s/it]
ChatCompletion(id='chatcmpl-9MyGMAw3UesYBVI650uz1CIPP0yly', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["child account age", "age requirement", "account eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715261894, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["child account age", "age requirement", "account eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How old does my kids need to be to open an account?"

Keyphrases:
517it [11:07,  1.84s/it]
ChatCompletion(id='chatcmpl-9MyGOnO2mnmv1mQ8cVBQfSuCr7IWY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["child account requirements", "minimum age for account", "youth banking account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261896, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["child account requirements", "minimum age for account", "youth banking account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How young can someone be in order to open an account?"

Keyphrases:
518it [11:09,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyGQeJkWXhp1Q7xZZgALZUlYW5yh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["minimum age for account", "account age requirement", "youth account eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715261898, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["minimum age for account", "account age requirement", "youth account eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the youngest someone can be to open an account?"

Keyphrases:
519it [11:11,  1.86s/it]
ChatCompletion(id='chatcmpl-9MyGS3jhuFmgQ9NDXFSH1GcU72MRr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["minimum age requirement", "account opening age", "youth account eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715261900, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["minimum age requirement", "account opening age", "youth account eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How old does one have to be to have an account with the bank?"

Keyphrases:
520it [11:13,  1.94s/it]
ChatCompletion(id='chatcmpl-9MyGUtHpamqlVfK9D5izJdG0Cv3ay', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account eligibility", "age requirement", "minimum age for bank account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261902, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["account eligibility", "age requirement", "minimum age for bank account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I get my PIN unlocked?"

Keyphrases:
521it [11:15,  1.82s/it]
ChatCompletion(id='chatcmpl-9MyGWk9NHH8oQiGAAwpAdV3TNJHjR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN unlock", "reset PIN", "security"]', role='assistant', function_call=None, tool_calls=None))], created=1715261904, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=11, prompt_tokens=226, total_tokens=237))
["PIN unlock", "reset PIN", "security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I view my PIN?"

Keyphrases:
522it [11:16,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyGX7cqhVVvyMq3q5dFdo1wWIkpA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN retrieval", "view PIN", "access PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715261905, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["PIN retrieval", "view PIN", "access PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will you reinstate my PIN?"

Keyphrases:
523it [11:22,  3.03s/it]
ChatCompletion(id='chatcmpl-9MyGZxbk9EZ9TJ4jF3hShZqXg4yh5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset PIN", "reinstate PIN", "PIN issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261907, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["reset PIN", "reinstate PIN", "PIN issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I accidentally blocked my PIN. How do I reset it?"

Keyphrases:
524it [11:24,  2.63s/it]
ChatCompletion(id='chatcmpl-9MyGfB1ayuo2jNNGpoWCx9gnUz2Dy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN reset", "unblock PIN", "reset blocked PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715261913, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["PIN reset", "unblock PIN", "reset blocked PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I unblock my pin after entering it wrong too many times?"

Keyphrases:
525it [11:26,  2.44s/it]
ChatCompletion(id='chatcmpl-9MyGgyGCOtGAvqx4J9qUjwJm1INGN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unblock PIN", "incorrect PIN entry", "reset PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715261914, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["unblock PIN", "incorrect PIN entry", "reset PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I used the wrong ping too many times and now the account is blocked.  How do I unblock?"

Keyphrases:
526it [11:29,  2.61s/it]
ChatCompletion(id='chatcmpl-9MyGiT2bDsnMQGoIwzE7q92x81UN4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account blocked", "unblock account", "incorrect PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715261916, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=240, total_tokens=253))
["account blocked", "unblock account", "incorrect PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need help because I drunken blocked my card?"

Keyphrases:
527it [11:31,  2.24s/it]
ChatCompletion(id='chatcmpl-9MyGl1r68vPdBb3ZoN53WedMon5Vd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card block", "emergency support", "accidental block"]', role='assistant', function_call=None, tool_calls=None))], created=1715261919, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["card block", "emergency support", "accidental block"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I reset my PIN, I can't seem to use my card?"

Keyphrases:
528it [11:32,  2.12s/it]
ChatCompletion(id='chatcmpl-9MyGny46kFMKFTvc8go7ns6JOabE5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN reset", "card issue resolution", "change PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715261921, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["PIN reset", "card issue resolution", "change PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When I put the wrong pin too much, I got blocked, so can you help me unblock my pin"

Keyphrases:
529it [11:34,  1.94s/it]
ChatCompletion(id='chatcmpl-9MyGpzCQd9Rksvk2nkpDZPg8waNwy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin unblock", "incorrect pin", "account blocked"]', role='assistant', function_call=None, tool_calls=None))], created=1715261923, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=241, total_tokens=254))
["pin unblock", "incorrect pin", "account blocked"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My pin was blocked, how do I make it so I can use it?"

Keyphrases:
530it [11:35,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyGqtUOD5L9g62w0uvsW8MZiOi59', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin blocked", "reset pin", "unblock pin"]', role='assistant', function_call=None, tool_calls=None))], created=1715261924, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["pin blocked", "reset pin", "unblock pin"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many tries do I have to enter my pin before I'm blocked?"

Keyphrases:
531it [11:38,  2.08s/it]
ChatCompletion(id='chatcmpl-9MyGtnGioaaVHiWxubGFO3JTItLgE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin entry limit", "account lock", "failed pin attempts"]', role='assistant', function_call=None, tool_calls=None))], created=1715261927, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["pin entry limit", "account lock", "failed pin attempts"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What should I do if I've tried to enter my PIN too often?"

Keyphrases:
532it [11:40,  2.06s/it]
ChatCompletion(id='chatcmpl-9MyGuQRFLBKDDAHRjuWTA0Qq1fgMs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN entry failed", "exceeded PIN attempts", "locked account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261928, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["PIN entry failed", "exceeded PIN attempts", "locked account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have exceeded the number of times I can try my PIN"

Keyphrases:
533it [11:41,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyGwfvfSNEGxiSMv4Z27TidtZLu8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN attempts exceeded", "PIN locked", "security restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715261930, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["PIN attempts exceeded", "PIN locked", "security restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I unblock a blocked pin number for my account?"

Keyphrases:
534it [11:43,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyGyMhgoBhYwtWsPlLImM1WqH2Wx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unblock pin", "reset pin", "blocked account access"]', role='assistant', function_call=None, tool_calls=None))], created=1715261932, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["unblock pin", "reset pin", "blocked account access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do if the bank machine won't accept my PIN attempts anymore?"

Keyphrases:
535it [11:44,  1.53s/it]
ChatCompletion(id='chatcmpl-9MyGzJcprPjBZ9az3Kq0zAb3xyDls', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN issues", "ATM access problem", "blocked PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715261933, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["PIN issues", "ATM access problem", "blocked PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you unlock my pin? I think I entered the wrong pin too many times."

Keyphrases:
536it [11:46,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyH0uxbN7QeaKgzFQSTsN1hdpjYy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unlock pin", "incorrect pin attempts", "reset pin"]', role='assistant', function_call=None, tool_calls=None))], created=1715261934, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=235, total_tokens=248))
["unlock pin", "incorrect pin attempts", "reset pin"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I deal with a blocked PIN?"

Keyphrases:
537it [11:49,  2.04s/it]
ChatCompletion(id='chatcmpl-9MyH2Z1iVyYlD2wmlyoAhLASUeUkS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["blocked PIN", "PIN issues", "unblocking PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715261936, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["blocked PIN", "PIN issues", "unblocking PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I attempted to use my card while I was intoxicated, and I failed to input my PIN, and the machine kept my card. How soon can I have it back?"

Keyphrases:
538it [11:53,  2.69s/it]
ChatCompletion(id='chatcmpl-9MyH51m3fd1REqH62b0hfQguiDEh1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card retrieval", "PIN entry failure", "card kept by machine"]', role='assistant', function_call=None, tool_calls=None))], created=1715261939, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=252, total_tokens=267))
["card retrieval", "PIN entry failure", "card kept by machine"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I unblock my card using the app?"

Keyphrases:
539it [11:59,  3.54s/it]
ChatCompletion(id='chatcmpl-9MyH9aYgZSjRrfOpy56Fz1hPiJgur', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unblock card", "card management", "use app to unblock"]', role='assistant', function_call=None, tool_calls=None))], created=1715261943, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["unblock card", "card management", "use app to unblock"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'v exhausted all the of times I can try my PIN"

Keyphrases:
540it [12:00,  3.07s/it]
ChatCompletion(id='chatcmpl-9MyHFjRQeh28YA1LGE3PvXocqOZ1G', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN attempts", "PIN locked", "exceeded PIN tries"]', role='assistant', function_call=None, tool_calls=None))], created=1715261949, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["PIN attempts", "PIN locked", "exceeded PIN tries"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I unlock my pin from too many tries?"

Keyphrases:
541it [12:02,  2.74s/it]
ChatCompletion(id='chatcmpl-9MyHHfPbmTMzmVyNaJfNzPOUDWck4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin unlock", "reset pin", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715261951, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["pin unlock", "reset pin", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help! I forgot my PIN and have been locked out of using my card."

Keyphrases:
542it [12:04,  2.27s/it]
ChatCompletion(id='chatcmpl-9MyHJLP1TMOtQW0Gpl0rflYvzNZZ0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["forgot PIN", "account locked", "PIN reset"]', role='assistant', function_call=None, tool_calls=None))], created=1715261953, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=234, total_tokens=246))
["forgot PIN", "account locked", "PIN reset"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My account is blocked, how do I log in now"

Keyphrases:
543it [12:05,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyHKj0wPWvQP8WPVqu0cNQAjSTHu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account blocked", "unblock account", "login issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261954, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["account blocked", "unblock account", "login issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I get blocked?"

Keyphrases:
544it [12:06,  1.71s/it]
ChatCompletion(id='chatcmpl-9MyHLvdt4kLA9WFnZpIE6UyS8iiae', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account blocked", "account suspension", "why blocked"]', role='assistant', function_call=None, tool_calls=None))], created=1715261955, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["account blocked", "account suspension", "why blocked"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are you able to unblock my pin?"

Keyphrases:
545it [12:07,  1.53s/it]
ChatCompletion(id='chatcmpl-9MyHM8YhkWTiXadMRiwKSOsLhvj8P', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unblock pin", "pin reset", "pin issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715261956, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["unblock pin", "pin reset", "pin issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you assist me with unblocking my PIN? I put it in wrong too many times."

Keyphrases:
546it [12:08,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyHN7OFHAL7EQuXfM9rLyFFGsgnM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unblock PIN", "PIN reset", "incorrect PIN attempts"]', role='assistant', function_call=None, tool_calls=None))], created=1715261957, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=237, total_tokens=251))
["unblock PIN", "PIN reset", "incorrect PIN attempts"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I entered the wrong pin too many times and now I am blocked.  Help me unblock!"

Keyphrases:
547it [12:10,  1.51s/it]
ChatCompletion(id='chatcmpl-9MyHPO0UOIyKaCwd5VXjw34kDlMgt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin blocked", "unblock account", "incorrect pin attempts"]', role='assistant', function_call=None, tool_calls=None))], created=1715261959, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=238, total_tokens=252))
["pin blocked", "unblock account", "incorrect pin attempts"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My pins seems to be blocked, can you unblock it please"

Keyphrases:
548it [12:11,  1.44s/it]
ChatCompletion(id='chatcmpl-9MyHQP5mVfQC945NclZuvO7D026J9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin blocked", "unblock pin", "security issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715261960, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["pin blocked", "unblock pin", "security issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you unblock my pin after too many wrong pin attempts?"

Keyphrases:
549it [12:17,  2.68s/it]
ChatCompletion(id='chatcmpl-9MyHSLuH9K1b0tLm6cQwbqYADgTnj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unblock pin", "pin reset", "failed pin attempts"]', role='assistant', function_call=None, tool_calls=None))], created=1715261962, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["unblock pin", "pin reset", "failed pin attempts"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What can you do to unblock my pin?"

Keyphrases:
550it [12:20,  2.90s/it]
ChatCompletion(id='chatcmpl-9MyHXgbW9crRoCfOBHOQRiiWsoaHD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin unblocking", "reset pin", "unblock card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261967, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["pin unblocking", "reset pin", "unblock card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My PIN is blocked, what do I do?"

Keyphrases:
551it [12:23,  2.76s/it]
ChatCompletion(id='chatcmpl-9MyHbjCoqRPvSdaapvopYMAyHKHRG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN blocked", "unblock PIN", "reset PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715261971, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["PIN blocked", "unblock PIN", "reset PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I reactivate my PIN?"

Keyphrases:
552it [12:26,  2.81s/it]
ChatCompletion(id='chatcmpl-9MyHd9gxSyrdbLP4ApBO0neEsAYvo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reactivate PIN", "reset PIN", "PIN activation"]', role='assistant', function_call=None, tool_calls=None))], created=1715261973, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["reactivate PIN", "reset PIN", "PIN activation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I reset my PIN?"

Keyphrases:
553it [12:27,  2.44s/it]
ChatCompletion(id='chatcmpl-9MyHgf8imWMTm5coIQPga7NQWAfGI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN reset", "change PIN", "reset password"]', role='assistant', function_call=None, tool_calls=None))], created=1715261976, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["PIN reset", "change PIN", "reset password"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I unblock my pin?"

Keyphrases:
554it [12:30,  2.50s/it]
ChatCompletion(id='chatcmpl-9MyHhP3Wsc6bhd2tzBCXMpOCosPn0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin unblocking", "reset pin", "unblock card pin"]', role='assistant', function_call=None, tool_calls=None))], created=1715261977, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["pin unblocking", "reset pin", "unblock card pin"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I unblock my PIN?"

Keyphrases:
555it [12:31,  2.08s/it]
ChatCompletion(id='chatcmpl-9MyHk8MJ4vfnf2PkqeIxF5dA9LELi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unblock PIN", "PIN reset", "reset account PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715261980, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["unblock PIN", "PIN reset", "reset account PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card's frozen, what can I do?"

Keyphrases:
556it [12:34,  2.46s/it]
ChatCompletion(id='chatcmpl-9MyHlu6WHhyCdtx48una6PG4V5DG5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card frozen", "unfreeze card", "troubleshoot frozen card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261981, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["card frozen", "unfreeze card", "troubleshoot frozen card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I unlock the pin?"

Keyphrases:
557it [12:36,  2.21s/it]
ChatCompletion(id='chatcmpl-9MyHptF5ctoPSjzcfWFuubiArW6ki', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin unlock", "reset pin", "unlock account"]', role='assistant', function_call=None, tool_calls=None))], created=1715261985, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["pin unlock", "reset pin", "unlock account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Since my pin is blocked, would you help me unblock it?"

Keyphrases:
558it [12:38,  2.06s/it]
ChatCompletion(id='chatcmpl-9MyHq1I4g8ts2C52yajEDi1Q02Kml', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin unblock", "blocked pin assistance", "reset pin"]', role='assistant', function_call=None, tool_calls=None))], created=1715261986, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["pin unblock", "blocked pin assistance", "reset pin"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My PIN is not working and I need assistance."

Keyphrases:
559it [12:40,  2.03s/it]
ChatCompletion(id='chatcmpl-9MyHsun97m5I5AAeAKUCZJfPrdmbJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN issues", "PIN not working", "assistance with PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715261988, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["PIN issues", "PIN not working", "assistance with PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "
Where can I get my PIN unblocked?"

Keyphrases:
560it [12:41,  1.99s/it]
ChatCompletion(id='chatcmpl-9MyHudgHSrKhVb2m1HdOeyyyQjE5o', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN unblocking", "reset PIN", "unblock PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715261990, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["PIN unblocking", "reset PIN", "unblock PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are contactless payments enabled on my new card?"

Keyphrases:
561it [12:46,  2.61s/it]
ChatCompletion(id='chatcmpl-9MyHwWW6Zj2EKIa1GKjwftuUbMvJm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payments", "card features", "payment methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715261992, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["contactless payments", "card features", "payment methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My contanctless has stopped working"

Keyphrases:
562it [12:48,  2.53s/it]
ChatCompletion(id='chatcmpl-9MyI07PxdGJMWR44sl372YFnw3ly5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless issues", "contactless not working", "payment failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715261996, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["contactless issues", "contactless not working", "payment failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what is required documents for new card process ?"

Keyphrases:
563it [12:50,  2.33s/it]
ChatCompletion(id='chatcmpl-9MyI2IBNnCOc5ZWxEcLA5s3DaGi2v', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["required documents", "new card application", "documentation for card"]', role='assistant', function_call=None, tool_calls=None))], created=1715261998, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["required documents", "new card application", "documentation for card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't know what's wrong, my contactless stopped working. Tried it in a few different places today and it didn't work in any of them."

Keyphrases:
564it [12:55,  3.27s/it]
ChatCompletion(id='chatcmpl-9MyI4K6tam1x4RLcjriFoh8umP4Fu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless failure", "contactless not working", "troubleshoot contactless"]', role='assistant', function_call=None, tool_calls=None))], created=1715262000, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=18, prompt_tokens=250, total_tokens=268))
["contactless failure", "contactless not working", "troubleshoot contactless"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I get the contactless feature to work for my card?"

Keyphrases:
565it [12:57,  2.91s/it]
ChatCompletion(id='chatcmpl-9MyI9aQwrNXe5LKyCB8lp8RdkxLtx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless feature activation", "enable contactless", "contactless card setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715262005, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=232, total_tokens=249))
["contactless feature activation", "enable contactless", "contactless card setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to pay contactless at the bus today and it didn't work. Any ideas why?"

Keyphrases:
566it [12:58,  2.39s/it]
ChatCompletion(id='chatcmpl-9MyIBjih1juvVyLTezrHeie6bwvT7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payment issue", "payment failure", "bus payment problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262007, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=238, total_tokens=253))
["contactless payment issue", "payment failure", "bus payment problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've been unable to pay contactless with my card for over a week now. Is there a way to fix this issue?"

Keyphrases:
567it [13:00,  2.16s/it]
ChatCompletion(id='chatcmpl-9MyIDAp1ELfiNcQAuJx1Qz81f4jm5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payment issue", "card malfunction", "payment troubleshooting"]', role='assistant', function_call=None, tool_calls=None))], created=1715262009, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=244, total_tokens=258))
["contactless payment issue", "card malfunction", "payment troubleshooting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you know why my contactless won't work?"

Keyphrases:
568it [13:02,  1.99s/it]
ChatCompletion(id='chatcmpl-9MyIE7EV040EI5g4Uc14SJA1YOOk8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless issue", "contactless not working", "contactless payment problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262010, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["contactless issue", "contactless not working", "contactless payment problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My contactless payments have not been completed successfully."

Keyphrases:
569it [13:03,  1.78s/it]
ChatCompletion(id='chatcmpl-9MyIGksAZyyscH2TIpUIZU7GzjvqM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payment issue", "failed payment", "payment not completed"]', role='assistant', function_call=None, tool_calls=None))], created=1715262012, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["contactless payment issue", "failed payment", "payment not completed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I need to replace my card if it didn't work when I tried to pay contactless at the shop today?"

Keyphrases:
570it [13:05,  1.91s/it]
ChatCompletion(id='chatcmpl-9MyIHW0B7ycJwm9MMmXUxSxxnBmBm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "contactless payment issue", "replace card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262013, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=242, total_tokens=256))
["card malfunction", "contactless payment issue", "replace card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "For some reason my contactless has stopped working. I don't know what the problem is. What can I do?"

Keyphrases:
571it [13:08,  2.29s/it]
ChatCompletion(id='chatcmpl-9MyIKAlYF8jOOr1vcp9OvrD9eIRKA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless issue", "contactless not working", "troubleshoot contactless"]', role='assistant', function_call=None, tool_calls=None))], created=1715262016, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=242, total_tokens=260))
["contactless issue", "contactless not working", "troubleshoot contactless"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I couldn't use my contactless this morning, it wasn't accepted."

Keyphrases:
572it [13:10,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyINzCUNzmRTNB4BM4fOMG2blIT6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payment issue", "payment declined", "contactless not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715262019, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["contactless payment issue", "payment declined", "contactless not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Contactless isn't working for me"

Keyphrases:
573it [13:11,  1.89s/it]
ChatCompletion(id='chatcmpl-9MyIOsdbyb48ACTBzokOo0LndjOhN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payment issue", "contactless not working", "NFC issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262020, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["contactless payment issue", "contactless not working", "NFC issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why wouldn't the contactless payment work when I tried to pay at the bus today?"

Keyphrases:
574it [13:13,  1.71s/it]
ChatCompletion(id='chatcmpl-9MyIQ2oOvOQjDQgwwRqgKscIdMf8Y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payment issue", "payment failure", "bus payment problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262022, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["contactless payment issue", "payment failure", "bus payment problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I check my security settings to allow contactless pay?"

Keyphrases:
575it [13:15,  1.86s/it]
ChatCompletion(id='chatcmpl-9MyIRsHpdYu8olVQsu4w0tFRxeKNy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payment settings", "security settings", "modify security settings for contactless pay"]', role='assistant', function_call=None, tool_calls=None))], created=1715262023, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=19, prompt_tokens=231, total_tokens=250))
["contactless payment settings", "security settings", "modify security settings for contactless pay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What can I do if contactless doesn't work?"

Keyphrases:
576it [13:16,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyITwnT5THtNHOc8XSJusr3KnZcC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless issue", "contactless not working", "troubleshoot contactless"]', role='assistant', function_call=None, tool_calls=None))], created=1715262025, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=229, total_tokens=247))
["contactless issue", "contactless not working", "troubleshoot contactless"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Fix my contactless"

Keyphrases:
577it [13:20,  2.25s/it]
ChatCompletion(id='chatcmpl-9MyIU5R6RE5qBW2FNgMs6N4rK8ZiD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless not working", "repair contactless", "contactless issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262026, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=223, total_tokens=239))
["contactless not working", "repair contactless", "contactless issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I make my contactless work for the metro?"

Keyphrases:
578it [13:21,  2.00s/it]
ChatCompletion(id='chatcmpl-9MyIYsFP77yxHKtzMpG1FbvTWu3Qi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payment issue", "metro access", "contactless functionality"]', role='assistant', function_call=None, tool_calls=None))], created=1715262030, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["contactless payment issue", "metro access", "contactless functionality"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My contactless is not working"

Keyphrases:
579it [13:23,  1.91s/it]
ChatCompletion(id='chatcmpl-9MyIZ3vXzeDZnT6AAcBr3LrODyudT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless failure", "contactless not working", "payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262031, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["contactless failure", "contactless not working", "payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you help my fix my contactless?"

Keyphrases:
580it [13:24,  1.84s/it]
ChatCompletion(id='chatcmpl-9MyIb1TWEumVZRRXNMMPeeCUxRP5L', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless troubleshooting", "contactless not working", "fix contactless feature"]', role='assistant', function_call=None, tool_calls=None))], created=1715262033, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=227, total_tokens=244))
["contactless troubleshooting", "contactless not working", "fix contactless feature"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "For some reason my contactless won't work for me."

Keyphrases:
581it [13:26,  1.74s/it]
ChatCompletion(id='chatcmpl-9MyId6QEY7ZSpqhFXeWCZEruaRTf8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless issue", "contactless not working", "payment failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715262035, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["contactless issue", "contactless not working", "payment failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm unable to use contactless payments for purchases."

Keyphrases:
582it [13:28,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyIenF0USE4jHpNpPYcGlldxTH3p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payments", "payment issues", "contactless not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715262036, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["contactless payments", "payment issues", "contactless not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When I tried to pay for my bus ride, the contactless payment wouldn't work. How can I prevent this in the future?"

Keyphrases:
583it [13:30,  1.86s/it]
ChatCompletion(id='chatcmpl-9MyIgyIS3nntnU7A4VVPKQ1JemH47', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payment issue", "payment failure", "prevent payment issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715262038, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=245, total_tokens=260))
["contactless payment issue", "payment failure", "prevent payment issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The NFC payment wouldn't work on the bus today. Help?"

Keyphrases:
584it [13:31,  1.78s/it]
ChatCompletion(id='chatcmpl-9MyIiR9vJ056E8Vutxxxu0lWoHwbb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["NFC payment issue", "contactless payment failure", "mobile payment not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715262040, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=231, total_tokens=249))
["NFC payment issue", "contactless payment failure", "mobile payment not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I wanted to use my card contactless but it doesn't seem to be working, what could be the problem?"

Keyphrases:
585it [13:34,  1.94s/it]
ChatCompletion(id='chatcmpl-9MyIkocE8DmrPjWejQVa7eAFrs7Tx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless card issue", "card malfunction", "contactless not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715262042, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=241, total_tokens=257))
["contactless card issue", "card malfunction", "contactless not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I make contactless work"

Keyphrases:
586it [13:36,  2.03s/it]
ChatCompletion(id='chatcmpl-9MyImchGRjy3lDSIrvLWjWwZMpWyS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless setup", "enable contactless", "contactless payment issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715262044, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["contactless setup", "enable contactless", "contactless payment issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what is the charges for new card?"

Keyphrases:
587it [13:38,  1.94s/it]
ChatCompletion(id='chatcmpl-9MyIoCv1YbWYSRVcoZvL4fWC6HQaD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["new card fee", "card charges", "issuance fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715262046, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["new card fee", "card charges", "issuance fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The contactless I have won't work."

Keyphrases:
588it [13:39,  1.71s/it]
ChatCompletion(id='chatcmpl-9MyIqdJHHxmQTKUjVk4iHdGJhKtes', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless issue", "contactless malfunction", "contactless not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715262048, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["contactless issue", "contactless malfunction", "contactless not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why isn't my contactless not working?"

Keyphrases:
589it [13:41,  1.89s/it]
ChatCompletion(id='chatcmpl-9MyIre8P68m8scxjjjenL0kKDMyIg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless issue", "contactless failure", "payment not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715262049, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["contactless issue", "contactless failure", "payment not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I wanted to use my contactless at the metro today but it didn't accept it!"

Keyphrases:
590it [13:43,  1.82s/it]
ChatCompletion(id='chatcmpl-9MyIuuv85Jqjnw8jR3ykk8d6x0sF0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payment issue", "payment failure", "metro card acceptance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262052, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["contactless payment issue", "payment failure", "metro card acceptance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It didnt work when I tried to pay contactless at the bus today. Why?"

Keyphrases:
591it [13:45,  1.87s/it]
ChatCompletion(id='chatcmpl-9MyIvc4waMKM1PcXKt48EFvjuVBJz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payment issue", "payment failure", "transaction problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262053, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["contactless payment issue", "payment failure", "transaction problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am not able to do contactless."

Keyphrases:
592it [13:48,  2.12s/it]
ChatCompletion(id='chatcmpl-9MyIx1Y5Yjj2mGZmkQXd7qmk5kIHj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless issues", "contactless not working", "unable to use contactless"]', role='assistant', function_call=None, tool_calls=None))], created=1715262055, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=227, total_tokens=245))
["contactless issues", "contactless not working", "unable to use contactless"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I use contactless payments?"

Keyphrases:
593it [13:49,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyJ0bQSV5lyEgi0kTiBFym35lpSG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payment usage", "using contactless", "NFC payments methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715262058, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["contactless payment usage", "using contactless", "NFC payments methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help me with my contactless which isn't working."

Keyphrases:
594it [13:50,  1.77s/it]
ChatCompletion(id='chatcmpl-9MyJ2XcBTw7lU03PxPsBraNPvMnxw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless issue", "contactless not working", "contactless card problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262060, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["contactless issue", "contactless not working", "contactless card problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I fix a problem where contactless isn't working?"

Keyphrases:
595it [13:52,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyJ3AOrQHB85ssKIOmgv35jm4qT1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless issue", "contactless not working", "fix contactless"]', role='assistant', function_call=None, tool_calls=None))], created=1715262061, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["contactless issue", "contactless not working", "fix contactless"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I use contactless pay?"

Keyphrases:
596it [13:55,  1.98s/it]
ChatCompletion(id='chatcmpl-9MyJ5bor3c6vKbzhRxFyYxibKsHDc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless payment setup", "using contactless pay", "activate contactless"]', role='assistant', function_call=None, tool_calls=None))], created=1715262063, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["contactless payment setup", "using contactless pay", "activate contactless"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I enable contactless pay?"

Keyphrases:
597it [13:57,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyJ7oR0Os9qsVjGrBjweElfQqcS2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["enable contactless", "contactless payment setup", "set up NFC payments"]', role='assistant', function_call=None, tool_calls=None))], created=1715262065, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["enable contactless", "contactless payment setup", "set up NFC payments"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I need to make a regular payment before a contactless one?"

Keyphrases:
598it [14:00,  2.28s/it]
ChatCompletion(id='chatcmpl-9MyJAiXGP9evAwjaXbJMRmFsPrQSN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment requirements", "contactless payment setup", "regular payment policy"]', role='assistant', function_call=None, tool_calls=None))], created=1715262068, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["payment requirements", "contactless payment setup", "regular payment policy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I find out where my contactless works?"

Keyphrases:
599it [14:01,  2.07s/it]
ChatCompletion(id='chatcmpl-9MyJCvSNdob29DMwxDBRI38jDbbWr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["contactless compatibility", "contactless locations", "contactless acceptance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262070, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["contactless compatibility", "contactless locations", "contactless acceptance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Should i reinstall the payment app?"

Keyphrases:
600it [14:03,  1.85s/it]
ChatCompletion(id='chatcmpl-9MyJDjAvCyhysWixMf43gQasNDYe7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reinstall app", "payment app issues", "app troubleshooting"]', role='assistant', function_call=None, tool_calls=None))], created=1715262071, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["reinstall app", "payment app issues", "app troubleshooting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how much do you charge to accept transfers"

Keyphrases:
601it [14:04,  1.86s/it]
ChatCompletion(id='chatcmpl-9MyJFLyqmFE2ai24CpFRXKmgCxxnd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fees", "cost of receiving money", "transaction charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262073, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["transfer fees", "cost of receiving money", "transaction charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to make a transfer. How much does it cost?"

Keyphrases:
602it [14:06,  1.68s/it]
ChatCompletion(id='chatcmpl-9MyJHvt2EPpAW3FmFOWrRCWltbp1J', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer cost", "transaction fees", "financial transfer charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262075, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["transfer cost", "transaction fees", "financial transfer charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to make a transfer, what will the fee be?"

Keyphrases:
603it [14:08,  1.83s/it]
ChatCompletion(id='chatcmpl-9MyJIScviB5ZotR54eJ7sUZY5zh1T', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "cost of transfer", "transaction cost"]', role='assistant', function_call=None, tool_calls=None))], created=1715262076, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["transfer fee", "cost of transfer", "transaction cost"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I make a top-up are there charges applied?"

Keyphrases:
604it [14:10,  2.04s/it]
ChatCompletion(id='chatcmpl-9MyJKuVQcp8cl6tpnSMGZZV4kpQbM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up fees", "charges for topping up", "cost of top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262078, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["top-up fees", "charges for topping up", "cost of top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I also transfer with SWIFT?"

Keyphrases:
605it [14:12,  1.99s/it]
ChatCompletion(id='chatcmpl-9MyJN94T1E9jT1txT1C7JPOHZ45rB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SWIFT transfer", "international transfer options", "using SWIFT"]', role='assistant', function_call=None, tool_calls=None))], created=1715262081, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["SWIFT transfer", "international transfer options", "using SWIFT"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are SWIFT transfers accepted?"

Keyphrases:
606it [14:17,  2.90s/it]
ChatCompletion(id='chatcmpl-9MyJRSX8uPYKxSAeiApXp1ZWEUFBl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SWIFT transfer", "international transfer acceptance", "bank transfer types"]', role='assistant', function_call=None, tool_calls=None))], created=1715262085, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["SWIFT transfer", "international transfer acceptance", "bank transfer types"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to refill my account using SWIFT."

Keyphrases:
607it [14:20,  2.74s/it]
ChatCompletion(id='chatcmpl-9MyJUeSW0bTmU2Xm0NuVHGcqTPjJF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SWIFT transfer", "account refill", "international transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262088, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["SWIFT transfer", "account refill", "international transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I have to pay for topping up by transfer?"

Keyphrases:
608it [14:21,  2.33s/it]
ChatCompletion(id='chatcmpl-9MyJWwDttFdB6QZd9bwRVUcesuuu7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fees", "top-up charges", "payment for transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262090, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["transfer fees", "top-up charges", "payment for transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there any sort of fees involved for top of transfers?"

Keyphrases:
609it [14:22,  2.04s/it]
ChatCompletion(id='chatcmpl-9MyJXKgUbrV0Mv5yDpYZz7xL3CwLT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fees", "transaction costs", "fee inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715262091, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["transfer fees", "transaction costs", "fee inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to get a transfer from SWIFT?"

Keyphrases:
610it [14:24,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyJZ0PBEqcaBxSOmXHjnXOYsvOHn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SWIFT transfer", "international transfer", "bank wire transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262093, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["SWIFT transfer", "international transfer", "bank wire transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I have to pay any fees in order to receive money?"

Keyphrases:
611it [14:25,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyJa4w2BArBFoHdG2F6fgiWiJRaE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["receiving fees", "transaction fees", "money transfer charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262094, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["receiving fees", "transaction fees", "money transfer charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much am I charged to receive money?"

Keyphrases:
612it [14:27,  1.67s/it]
ChatCompletion(id='chatcmpl-9MyJbfdF08X1smnx2XebW2ZmniGxd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["receiving fees", "transaction charges", "money transfer costs"]', role='assistant', function_call=None, tool_calls=None))], created=1715262095, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["receiving fees", "transaction charges", "money transfer costs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will you deal with SWIFT transfers?"

Keyphrases:
613it [14:29,  1.99s/it]
ChatCompletion(id='chatcmpl-9MyJdrEXLY6e1tmGYBcLklts6aSm7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SWIFT transfer services", "international transfer options", "bank wire transfer availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715262097, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["SWIFT transfer services", "international transfer options", "bank wire transfer availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will there be any charges for money received?"

Keyphrases:
614it [14:32,  2.13s/it]
ChatCompletion(id='chatcmpl-9MyJgyrATXHXvllI2E3ikJEXOZ1wi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction fees", "receiving charges", "money transfer fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715262100, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["transaction fees", "receiving charges", "money transfer fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will a transfer incur a fee?"

Keyphrases:
615it [14:34,  2.00s/it]
ChatCompletion(id='chatcmpl-9MyJiOi7CqncxBJ6mhFAtSDCw0kQe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "fee inquiry", "cost of transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262102, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["transfer fee", "fee inquiry", "cost of transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there charges for receiving a SEPA transfer?"

Keyphrases:
616it [14:35,  1.86s/it]
ChatCompletion(id='chatcmpl-9MyJkClDk0GVy5oBRPfP589vTmljV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SEPA transfer fees", "receiving charges", "SEPA charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262104, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["SEPA transfer fees", "receiving charges", "SEPA charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I transfer money from my bank to top-up my account will I be charged?"

Keyphrases:
617it [14:37,  1.77s/it]
ChatCompletion(id='chatcmpl-9MyJlEaAw6pXj3rDoZ91IKMyhp0K8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fees", "bank transfer charges", "top-up charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262105, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["transfer fees", "bank transfer charges", "top-up charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will I be charged if someone needs to send me money?"

Keyphrases:
618it [14:38,  1.69s/it]
ChatCompletion(id='chatcmpl-9MyJnwGuc7HzMpATxmcWTXpzqHqCn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["receiving money fees", "transfer charges", "incoming transfer fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715262107, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["receiving money fees", "transfer charges", "incoming transfer fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the fees for top-ups?"

Keyphrases:
619it [14:40,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyJoZrId3qwPU5Q8FAqN79hue2IX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up fees", "account recharge cost", "transaction charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262108, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["top-up fees", "account recharge cost", "transaction charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will topping up by transfer lead to a charge on my account?"

Keyphrases:
620it [14:41,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyJqtUPgZzFC7rPrzxxVY97wXZLG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up charge", "transfer fee", "account charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715262110, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["top up charge", "transfer fee", "account charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the charges for receiving money?"

Keyphrases:
621it [14:45,  2.25s/it]
ChatCompletion(id='chatcmpl-9MyJrdj7XG1op4Z170vasHh1Jadid', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["receiving charges", "money transfer fees", "transaction costs"]', role='assistant', function_call=None, tool_calls=None))], created=1715262111, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["receiving charges", "money transfer fees", "transaction costs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the fee to receive money?"

Keyphrases:
622it [14:47,  2.15s/it]
ChatCompletion(id='chatcmpl-9MyJvg1EIPM2cn4r3ikXD8hgBoAk7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money receiving fee", "transaction fee", "transfer charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262115, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["money receiving fee", "transaction fee", "transfer charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much am I charged for a SEPA transfer?"

Keyphrases:
623it [14:49,  2.12s/it]
ChatCompletion(id='chatcmpl-9MyJx6bPDJMXqWj32fRi2LENRGMvs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SEPA transfer cost", "transfer fees", "SEPA charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262117, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["SEPA transfer cost", "transfer fees", "SEPA charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much is the fee for a SEPA transfer?"

Keyphrases:
624it [14:50,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyJzsLAdVFtmDrlmir6EvI7PUONL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SEPA transfer fee", "transfer costs", "international transfer charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262119, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["SEPA transfer fee", "transfer costs", "international transfer charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What'll it charge me for a SEPA transfer?"

Keyphrases:
625it [14:52,  1.91s/it]
ChatCompletion(id='chatcmpl-9MyK1xet3Wli9rtqSuz3CUITbd4YZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SEPA transfer cost", "transfer fees", "SEPA fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715262121, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["SEPA transfer cost", "transfer fees", "SEPA fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a charge for topping up by transfer?"

Keyphrases:
626it [14:54,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyK2HI11zq8d0aQKvM1l40WpXGJW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up fee", "transfer charge", "banking fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715262122, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top-up fee", "transfer charge", "banking fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you do SWIFT transfers?"

Keyphrases:
627it [14:55,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyK479hGw5uoasjAXhPZ7WSQurqg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SWIFT transfer availability", "international transfer options", "banking transfer methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715262124, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=225, total_tokens=242))
["SWIFT transfer availability", "international transfer options", "banking transfer methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Should I expect to be charged for topping up by transfer?"

Keyphrases:
628it [14:57,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyK6IozRQbBP4dxA2ReC2SvmkYXP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fees", "top-up charges", "bank transfer costs"]', role='assistant', function_call=None, tool_calls=None))], created=1715262126, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["transfer fees", "top-up charges", "bank transfer costs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will I be charged for a SEPA transfer?"

Keyphrases:
629it [14:59,  1.80s/it]
ChatCompletion(id='chatcmpl-9MyK7pZKpzlyyLTNDOe5w19sN2b3e', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SEPA transfer fee", "transfer charge", "cost of SEPA transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262127, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["SEPA transfer fee", "transfer charge", "cost of SEPA transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "is there a fee for a transfer? if so how much will it be?"

Keyphrases:
630it [15:02,  2.08s/it]
ChatCompletion(id='chatcmpl-9MyK9a5Up8dHl4EFJbxF0S23edQaq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fees", "cost of transfer", "transfer charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262129, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["transfer fees", "cost of transfer", "transfer charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please tell me about SWIFT transfers at this bank."

Keyphrases:
631it [15:04,  2.08s/it]
ChatCompletion(id='chatcmpl-9MyKC0rbiAzEo2tlaSlFhs9nCsLnZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SWIFT transfer details", "international transfer info", "bank wire transfer information"]', role='assistant', function_call=None, tool_calls=None))], created=1715262132, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["SWIFT transfer details", "international transfer info", "bank wire transfer information"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a fee for transfer top-up?"

Keyphrases:
632it [15:05,  2.00s/it]
ChatCompletion(id='chatcmpl-9MyKEIPvDOIHPZ8C8IzN6Pagb3XSU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "top-up charge", "banking fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715262134, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["transfer fee", "top-up charge", "banking fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me what the transfer policy is?"

Keyphrases:
633it [15:07,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyKGo0mgIMKU6Jc4nwJGSZjOH2p8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer policy", "banking policy", "transfer rules"]', role='assistant', function_call=None, tool_calls=None))], created=1715262136, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["transfer policy", "banking policy", "transfer rules"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is a SWIFT transfer okay?"

Keyphrases:
634it [15:08,  1.67s/it]
ChatCompletion(id='chatcmpl-9MyKHgkFByIs3oPOOE0SqpQDbFrlp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SWIFT transfer", "international transfer", "transfer method"]', role='assistant', function_call=None, tool_calls=None))], created=1715262137, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["SWIFT transfer", "international transfer", "transfer method"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will I be charged a fee if I receive a SEPA transfer"

Keyphrases:
635it [15:10,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyKIY7zcIBl5yftj1RjN1jQOZ12F', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SEPA transfer fee", "receiving fees", "transfer charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262138, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["SEPA transfer fee", "receiving fees", "transfer charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When topping up by transfer, will I be charged?"

Keyphrases:
636it [15:11,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyKK1nw5YVWdr7vH2nwdctve8Hmf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up charges", "transfer fees", "cost of topping up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262140, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["top up charges", "transfer fees", "cost of topping up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What us the fee to transfer money from my bank?"

Keyphrases:
637it [15:13,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyKLwdjT4clFSx8S4EscN6c3Hf2e', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "money transfer cost", "banking fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715262141, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["transfer fee", "money transfer cost", "banking fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I get charged if i am getting money?"

Keyphrases:
638it [15:15,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyKN7OmYS8kiDvQbP5ASLIXqODoM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["receiving charges", "money transfer fees", "incoming transaction cost"]', role='assistant', function_call=None, tool_calls=None))], created=1715262143, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["receiving charges", "money transfer fees", "incoming transaction cost"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me the total cost of a transfer?"

Keyphrases:
639it [15:16,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyKP3vWUZUXVzIL7Cpxg0WAEIxAs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer cost", "total transfer charges", "fee calculation"]', role='assistant', function_call=None, tool_calls=None))], created=1715262145, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["transfer cost", "total transfer charges", "fee calculation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "can i do a transfer with swift"

Keyphrases:
640it [15:18,  1.73s/it]
ChatCompletion(id='chatcmpl-9MyKRM0J4PM6D1r8okprvZzPoS4QX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["SWIFT transfer", "international transfer", "bank transfer method"]', role='assistant', function_call=None, tool_calls=None))], created=1715262147, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["SWIFT transfer", "international transfer", "bank transfer method"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "new customer and filling gas today, it's not working, the thing shows pending half an hour!"

Keyphrases:
641it [15:20,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyKT88lCjjhrldTIsBNiXYwrvyvx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["gas purchase issue", "transaction pending", "new customer support"]', role='assistant', function_call=None, tool_calls=None))], created=1715262149, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=238, total_tokens=252))
["gas purchase issue", "transaction pending", "new customer support"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card was topped this morning but I can't see the funds. Why didn't it complete?"

Keyphrases:
642it [15:22,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyKUpV2XaaeXjC4EbYPx1aOx7etQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issues", "funds not reflected", "missing funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715262150, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=238, total_tokens=253))
["top-up issues", "funds not reflected", "missing funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What would lead to my top up still pending?"

Keyphrases:
643it [15:24,  2.00s/it]
ChatCompletion(id='chatcmpl-9MyKWVIqTq0MTjcg9K8OiAkbyySRi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up status", "pending top up", "delay in balance update"]', role='assistant', function_call=None, tool_calls=None))], created=1715262152, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["top up status", "pending top up", "delay in balance update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "there's a delay in my top-up"

Keyphrases:
644it [15:26,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyKZ8ST5pSk5uNR4FuS3li0rjQnJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up delay", "account recharge issue", "recharge not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715262155, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["top-up delay", "account recharge issue", "recharge not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a reason my top up hasn't gone through"

Keyphrases:
645it [15:28,  1.83s/it]
ChatCompletion(id='chatcmpl-9MyKaqO2t1prZEDIAhIyWNvNaI1mi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "failed top up", "transaction problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262156, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["top up issue", "failed top up", "transaction problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The top-up is pending."

Keyphrases:
646it [15:30,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyKccsDxHrx0nLPD6TD6FW2VWUbr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending top-up", "transaction status", "delayed deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262158, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["pending top-up", "transaction status", "delayed deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Could you explain why my top-up has gone through yet?"

Keyphrases:
647it [15:31,  1.78s/it]
ChatCompletion(id='chatcmpl-9MyKe5Tur6A8eGlpAfxJ5GYZa6fPt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "pending top-up", "top-up confirmation"]', role='assistant', function_call=None, tool_calls=None))], created=1715262160, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["top-up status", "pending top-up", "top-up confirmation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've already topped up, but I cannot see the funds being available. What happened?"

Keyphrases:
648it [15:32,  1.59s/it]
ChatCompletion(id='chatcmpl-9MyKfLMazf8XuyXtVAUfzDTYx3TLQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "funds not available", "missing deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262161, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["top up issue", "funds not available", "missing deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is going on? My top-up is still pending. I use your system all the time but now it is just showing as pending."

Keyphrases:
649it [15:34,  1.58s/it]
ChatCompletion(id='chatcmpl-9MyKhd43P7MoMlkyefmBRXsaNACum', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "pending top-up", "transaction delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715262163, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=246, total_tokens=260))
["top-up status", "pending top-up", "transaction delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I  do not see a top-up processed."

Keyphrases:
650it [15:35,  1.48s/it]
ChatCompletion(id='chatcmpl-9MyKi5XtGNFPf2uy4sMv9oTQ88Duc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "missing top-up", "top-up not processed"]', role='assistant', function_call=None, tool_calls=None))], created=1715262164, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["top-up issue", "missing top-up", "top-up not processed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I topped up but it didn't complete"

Keyphrases:
651it [15:36,  1.41s/it]
ChatCompletion(id='chatcmpl-9MyKjRjrZAWz8wFLVfpt6NmpACexv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "transaction incomplete", "failed deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262165, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["top-up issue", "transaction incomplete", "failed deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "So, I am a new customer and attempted to top up for the very first time today. It's already been pending for half an hour and doesn't seem to be working. I need to please get this fixed."

Keyphrases:
652it [15:38,  1.49s/it]
ChatCompletion(id='chatcmpl-9MyKlIr9d9AAo4g7wFWupiQr7rNpV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "transaction pending", "first time top up problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262167, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=262, total_tokens=278))
["top up issue", "transaction pending", "first time top up problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top up is pending."

Keyphrases:
653it [15:41,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyKmkGmIgTOUOTTmgaH7CXVcPZui', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up status", "pending top up", "transaction pending"]', role='assistant', function_call=None, tool_calls=None))], created=1715262168, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["top up status", "pending top up", "transaction pending"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you look into my top up please.  I made it over three hours ago and yet it's still pending."

Keyphrases:
654it [15:42,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyKpi972t4OsWCtWfd5fYwq0532Z', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up status", "pending top up", "delayed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262171, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=242, total_tokens=257))
["top up status", "pending top up", "delayed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you please make my top up go through as soon as possible. I really need the money and it has been pending for an hour already."

Keyphrases:
655it [15:44,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyKrFH9j3whMk0OqTBhtEb7nhixy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["urgent top up", "pending top up", "expedite top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262173, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=247, total_tokens=264))
["urgent top up", "pending top up", "expedite top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What's going on with the top-up? All it says is pending, pending, pending! I use your service several times a week and have never had a problem before! What's going on here?"

Keyphrases:
656it [15:45,  1.64s/it]
ChatCompletion(id='chatcmpl-9MyKssq35jxAn1KylqcwkZPcTwatZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "pending top-up", "service delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715262174, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=259, total_tokens=273))
["top-up issue", "pending top-up", "service delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "why hasn't my top up gone through yet"

Keyphrases:
657it [15:47,  1.67s/it]
ChatCompletion(id='chatcmpl-9MyKuFDgukU6QqpMUMjgjHSWPVqzN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up status", "failed top up", "pending transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262176, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top up status", "failed top up", "pending transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "top-up is slow to process"

Keyphrases:
658it [15:49,  1.68s/it]
ChatCompletion(id='chatcmpl-9MyKvNkZfd9vCEunMYJhiIOv33IP7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up delay", "slow processing", "top-up status"]', role='assistant', function_call=None, tool_calls=None))], created=1715262177, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["top-up delay", "slow processing", "top-up status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there something wrong with your website? I tried topping up my account and it's been close to two hours now and it's still at "pending" for some reason. I just joined with you guys and this is the first attempt at this, so maybe I'm wrong, but shouldn't this be instant?"

Keyphrases:
659it [15:50,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyKx2AJer4NI1TL5SGuXvabHGaDU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["website issue", "top-up pending", "account recharge delay", "transaction status"]', role='assistant', function_call=None, tool_calls=None))], created=1715262179, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=18, prompt_tokens=281, total_tokens=299))
["website issue", "top-up pending", "account recharge delay", "transaction status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I topped up by card a while ago and it's still pending, surely it should be done by now?"

Keyphrases:
660it [15:52,  1.50s/it]
ChatCompletion(id='chatcmpl-9MyKzRF0Y0cOpluw8vV0g1ShBHQed', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "pending transaction", "card top-up delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715262181, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=240, total_tokens=255))
["top-up status", "pending transaction", "card top-up delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why hasn't my top-up been completed?"

Keyphrases:
661it [15:54,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyL0KV1VKqc1Mc73g8oGUuGMAnB0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "top-up issue", "pending top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262182, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["top-up status", "top-up issue", "pending top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "top up did not complete"

Keyphrases:
662it [15:56,  1.84s/it]
ChatCompletion(id='chatcmpl-9MyL22f5c9LpuFShJslm6b4zMgTld', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up failure", "recharge unsuccessful", "balance not updated"]', role='assistant', function_call=None, tool_calls=None))], created=1715262184, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["top up failure", "recharge unsuccessful", "balance not updated"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "So I just put my top-up into the card and it hasn't changed."

Keyphrases:
663it [15:58,  1.98s/it]
ChatCompletion(id='chatcmpl-9MyL4x0dI3A6PQyPNZ1Ntg2ix07oi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "balance not updated", "funds not credited"]', role='assistant', function_call=None, tool_calls=None))], created=1715262186, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=234, total_tokens=250))
["top-up issue", "balance not updated", "funds not credited"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my top up still pending?"

Keyphrases:
664it [16:00,  1.83s/it]
ChatCompletion(id='chatcmpl-9MyL65XPBW5IDoKUBRIgcfXaDpBzk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending top up", "top up not credited", "delayed balance update"]', role='assistant', function_call=None, tool_calls=None))], created=1715262188, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["pending top up", "top up not credited", "delayed balance update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Your top-up function isn't working, it still says pending even though I know my card works."

Keyphrases:
665it [16:01,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyL8K0hPSAlj4j4PkyWVxvznKWSG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "pending top-up", "top-up not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715262190, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=238, total_tokens=254))
["top-up issue", "pending top-up", "top-up not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hi I'm a new customer and tried topping up for the first time today, seems it's not working, the thing shows up as pending since half an hour already! Please fix it!"

Keyphrases:
666it [16:04,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyLACl9zlaQWXcKzQjpZBgMmn51a', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "pending transaction", "first-time top-up problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262192, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=256, total_tokens=272))
["top-up issue", "pending transaction", "first-time top-up problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "OMG!  I'm trying to load my card and it wont top up!  I desperately need the money either on my card or in my bank, where is it?"

Keyphrases:
667it [16:08,  2.80s/it]
ChatCompletion(id='chatcmpl-9MyLCt6x3rxxF4ZTZ8fkpodgGPQKE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card top-up issue", "urgent fund transfer", "missing funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715262194, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=254, total_tokens=269))
["card top-up issue", "urgent fund transfer", "missing funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm attempting to top-up my account but it has been pending for an hour."

Keyphrases:
668it [16:10,  2.39s/it]
ChatCompletion(id='chatcmpl-9MyLHiRj0Lsjqm7Zp4MtCr8gHYUsd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up pending", "account recharge delay", "transaction pending"]', role='assistant', function_call=None, tool_calls=None))], created=1715262199, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["top-up pending", "account recharge delay", "transaction pending"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my top-up still outstanding?"

Keyphrases:
669it [16:12,  2.34s/it]
ChatCompletion(id='chatcmpl-9MyLIWPg9yIVT4WgjzcGSHOBsYM3K', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "pending top-up", "outstanding balance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262200, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["top-up status", "pending top-up", "outstanding balance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What does it mean when my top up is saying  still pending?"

Keyphrases:
670it [16:14,  2.10s/it]
ChatCompletion(id='chatcmpl-9MyLKsMzegc2dIwNBRuQBM5KXbyZq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending top up", "top up status", "transaction pending"]', role='assistant', function_call=None, tool_calls=None))], created=1715262202, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["pending top up", "top up status", "transaction pending"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top up hasn't worked, it's been stuck in pending for the last couple hours"

Keyphrases:
671it [16:15,  1.91s/it]
ChatCompletion(id='chatcmpl-9MyLMpdaHRPOxSJSZaiBPy5xzRBKH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "pending transaction", "transaction not completed"]', role='assistant', function_call=None, tool_calls=None))], created=1715262204, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=237, total_tokens=251))
["top up issue", "pending transaction", "transaction not completed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It doesn't look like the top-up completed."

Keyphrases:
672it [16:16,  1.73s/it]
ChatCompletion(id='chatcmpl-9MyLNaR1DLAaIWyRo3WLqJhPgv6qT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "failed top-up", "transaction completion"]', role='assistant', function_call=None, tool_calls=None))], created=1715262205, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top-up status", "failed top-up", "transaction completion"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why does my top up say still pending when I used my card to do it."

Keyphrases:
673it [16:18,  1.69s/it]
ChatCompletion(id='chatcmpl-9MyLP4sK0fCHMVc44iBbljxOUp0U7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up pending", "card top up status", "pending transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262207, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=235, total_tokens=250))
["top up pending", "card top up status", "pending transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is the money I topped off with?"

Keyphrases:
674it [16:19,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyLQFBYLePuSI8IfxJKUD0XGyex8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "money not received", "transaction status"]', role='assistant', function_call=None, tool_calls=None))], created=1715262208, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["top-up status", "money not received", "transaction status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hi. I'm a new customer to your system and I think something isn't working right - or maybe it is. Maybe you can confirm. I tried to top up today (my first time ever) and it's been stuck at "pending" for over an hour now. Is it supposed to do this or is there something wrong in the system?"

Keyphrases:
675it [16:22,  1.97s/it]
ChatCompletion(id='chatcmpl-9MyLSEIqmzpmVEvMmtu2c346hYxPs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "pending transaction", "transaction status"]', role='assistant', function_call=None, tool_calls=None))], created=1715262210, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=289, total_tokens=302))
["top up issue", "pending transaction", "transaction status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my top-up still pending?"

Keyphrases:
676it [16:24,  1.86s/it]
ChatCompletion(id='chatcmpl-9MyLUaoXBrOsfLkl1d8b4rM5D1Yl0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending top-up", "top-up status", "delay in top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262212, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["pending top-up", "top-up status", "delay in top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Topping up my card is not working because I believe the top up is pending"

Keyphrases:
677it [16:26,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyLWvySsVpfIgAkM03lDM4Grig7T', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "pending top up", "card recharge problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262214, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=235, total_tokens=250))
["top up issue", "pending top up", "card recharge problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will my top-up process?"

Keyphrases:
678it [16:29,  2.32s/it]
ChatCompletion(id='chatcmpl-9MyLYTU8iwGt413bC7xTQpWvLzrbB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "processing time", "transaction completion"]', role='assistant', function_call=None, tool_calls=None))], created=1715262216, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["top-up status", "processing time", "transaction completion"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The top-up has a definite problem! I regularly use your service and haven't had a problem before, but now the top-up just shows pending. Please tell my why it continues to show pending."

Keyphrases:
679it [16:30,  1.99s/it]
ChatCompletion(id='chatcmpl-9MyLbCUPjoF9U0VLnUyRMuP2hJ5xh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "pending top-up", "top-up status"]', role='assistant', function_call=None, tool_calls=None))], created=1715262219, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=258, total_tokens=273))
["top-up issue", "pending top-up", "top-up status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried topping up but my funds seem to be pending. I want to buy something right now, what do I do?"

Keyphrases:
680it [16:32,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyLdwg23UxUBkXJxS8FBKFSyoIVK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending funds", "top-up issue", "immediate funds access"]', role='assistant', function_call=None, tool_calls=None))], created=1715262221, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=243, total_tokens=258))
["pending funds", "top-up issue", "immediate funds access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a transaction this morning and would like to revert it."

Keyphrases:
681it [16:33,  1.65s/it]
ChatCompletion(id='chatcmpl-9MyLeZci3bGtIWgWKGi8udOsnEOtv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reverse transaction", "undo transaction", "transaction cancellation"]', role='assistant', function_call=None, tool_calls=None))], created=1715262222, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["reverse transaction", "undo transaction", "transaction cancellation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can i cancel a charge?"

Keyphrases:
682it [16:34,  1.46s/it]
ChatCompletion(id='chatcmpl-9MyLfseGFS0EUTrHvrghjkqy3IRtV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel charge", "reverse transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262223, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=8, prompt_tokens=224, total_tokens=232))
["cancel charge", "reverse transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I cancel my transaction?"

Keyphrases:
683it [16:35,  1.38s/it]
ChatCompletion(id='chatcmpl-9MyLgRlkTb6sbIKjFQtqIyoYqOyh1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transaction", "transaction reversal", "stop payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715262224, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["cancel transaction", "transaction reversal", "stop payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a transaction but did it to the wrong account."

Keyphrases:
684it [16:37,  1.44s/it]
ChatCompletion(id='chatcmpl-9MyLhQraNTGqgzQ49Gd3iUcRv7m4C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["wrong transaction", "misdirected transfer", "correcting a payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715262225, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["wrong transaction", "misdirected transfer", "correcting a payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Tell me how to cancel a transfer."

Keyphrases:
685it [16:39,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyLjww4TuOekk3pCUndcbbl7wyC6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transfer", "stop payment", "revoke transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262227, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["cancel transfer", "stop payment", "revoke transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need you to cancel a transfer that I made.  It is the wrong account number and the app won't let me stop the transaction.  Please stop it!"

Keyphrases:
686it [16:40,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyLl2GceZ0nfQFwnHgfIb32QIwS4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transfer", "stop transaction", "wrong account transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262229, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=252, total_tokens=265))
["cancel transfer", "stop transaction", "wrong account transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to cancel my recent transfer immediately, I made a mistake there, please help quickly before it goes through"

Keyphrases:
687it [16:41,  1.46s/it]
ChatCompletion(id='chatcmpl-9MyLmMlktUIFObptylSaasKkooImH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transfer", "urgent transfer cancellation", "reverse transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262230, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=241, total_tokens=254))
["cancel transfer", "urgent transfer cancellation", "reverse transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to revert a transaction I did this morning"

Keyphrases:
688it [16:42,  1.37s/it]
ChatCompletion(id='chatcmpl-9MyLoiqKf5VYFK1wiTM8VBFt4V1tD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["revert transaction", "undo transaction", "transaction reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262232, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["revert transaction", "undo transaction", "transaction reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I make a transaction can I cancel it?"

Keyphrases:
689it [16:44,  1.44s/it]
ChatCompletion(id='chatcmpl-9MyLpw5dloyZxuAgCP2FdtrZygpPk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction cancellation", "cancel transaction", "reversing transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262233, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["transaction cancellation", "cancel transaction", "reversing transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I cancel a transfer?"

Keyphrases:
690it [16:45,  1.37s/it]
ChatCompletion(id='chatcmpl-9MyLqPZVA3A57VVklztZ6ySYaLHtp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transfer", "stop payment", "revoke transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262234, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["cancel transfer", "stop payment", "revoke transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there any way to cancel a transfer?"

Keyphrases:
691it [16:47,  1.39s/it]
ChatCompletion(id='chatcmpl-9MyLsTLRyNEFer1xThbYRBryxIOUl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transfer", "revoke transaction", "stop payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715262236, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["cancel transfer", "revoke transaction", "stop payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I accidentally made a transaction to the wrong account."

Keyphrases:
692it [16:48,  1.39s/it]
ChatCompletion(id='chatcmpl-9MyLtPver8i8J5TtOAMigLoQ0TK7c', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["wrong transaction", "transaction reversal", "misdirected funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715262237, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["wrong transaction", "transaction reversal", "misdirected funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to cancel a transfer right away! Can you help?"

Keyphrases:
693it [16:49,  1.35s/it]
ChatCompletion(id='chatcmpl-9MyLuwcpzeXxybBhvDeAZ9po1RA3d', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transfer", "stop payment", "urgent transfer cancellation"]', role='assistant', function_call=None, tool_calls=None))], created=1715262238, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["cancel transfer", "stop payment", "urgent transfer cancellation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help me cancel my transaction"

Keyphrases:
694it [16:51,  1.37s/it]
ChatCompletion(id='chatcmpl-9MyLwhuMQaR3gRjG854fqdi3X4zJ0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transaction", "transaction reversal", "stop payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715262240, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["cancel transaction", "transaction reversal", "stop payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "This is URGENT, I typed the wrong payment information for a payment I needed to make and have clicked send, I need to reverse the transaction immediately."

Keyphrases:
695it [16:53,  1.63s/it]
ChatCompletion(id='chatcmpl-9MyLxQgqq68y9IQJfsNF1c1s8Y0Oa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reverse transaction", "incorrect payment details", "urgent payment reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262241, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=250, total_tokens=264))
["reverse transaction", "incorrect payment details", "urgent payment reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I cancel a transfer"

Keyphrases:
696it [16:54,  1.48s/it]
ChatCompletion(id='chatcmpl-9MyLz7fDfyL1oAmWuGqv9bmIPB94D', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transfer", "stop payment", "reverse transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262243, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["cancel transfer", "stop payment", "reverse transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to reverse my transaction from earlier"

Keyphrases:
697it [16:55,  1.34s/it]
ChatCompletion(id='chatcmpl-9MyM08m9hl2UP5XHKtPZdWSWjblSp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reverse transaction", "transaction reversal", "undo transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262244, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["reverse transaction", "transaction reversal", "undo transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a way to revert my transaction from this morning?"

Keyphrases:
698it [16:58,  1.85s/it]
ChatCompletion(id='chatcmpl-9MyM2tuLz6WbHavnVI6uRZLc7FthH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["revert transaction", "undo transaction", "transaction reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262246, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["revert transaction", "undo transaction", "transaction reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'd like to cancel a transfer"

Keyphrases:
699it [17:00,  1.71s/it]
ChatCompletion(id='chatcmpl-9MyM595fhMU3yuFEAV8b4vfR87OeD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transfer", "stop payment", "reverse transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262249, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["cancel transfer", "stop payment", "reverse transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I cancel a transfer if is already processed?"

Keyphrases:
700it [17:01,  1.55s/it]
ChatCompletion(id='chatcmpl-9MyM6MYr7Bc7dYCg1bhxvLd8PlZCj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel processed transfer", "reverse transfer", "transaction reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262250, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["cancel processed transfer", "reverse transfer", "transaction reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I transferred the wrong amount and would like to cancel the transaction."

Keyphrases:
701it [17:04,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyM7jpy9HAGUAU9NExSTjbQxDbfr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transaction", "incorrect transfer amount", "reverse payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715262251, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["cancel transaction", "incorrect transfer amount", "reverse payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a mistake when I did a transfer so now what can I do to fix that?"

Keyphrases:
702it [17:05,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyMAlIYi7cf4jX7zOadZMvkafSho', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["correct transfer error", "undo transfer", "transfer mistake resolution"]', role='assistant', function_call=None, tool_calls=None))], created=1715262254, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=237, total_tokens=251))
["correct transfer error", "undo transfer", "transfer mistake resolution"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to cancel an incorrect transaction."

Keyphrases:
703it [17:08,  2.02s/it]
ChatCompletion(id='chatcmpl-9MyMBic5wCuZ7s1w3VTxFbLmNzYjT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transaction", "reverse transaction", "incorrect charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715262255, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["cancel transaction", "reverse transaction", "incorrect charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I cancel my transfer?"

Keyphrases:
704it [17:09,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyMELN97yxCaJAnZ65vAkh4DAKPm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transfer", "stop payment", "revoke transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262258, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["cancel transfer", "stop payment", "revoke transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a mistake with a transaction!"

Keyphrases:
705it [17:10,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyMFUvjVKhxpTZMHyODfBoSD1xLb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction error", "correct transaction", "transaction mistake"]', role='assistant', function_call=None, tool_calls=None))], created=1715262259, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["transaction error", "correct transaction", "transaction mistake"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I submitted a transaction to the incorrect account."

Keyphrases:
706it [17:12,  1.56s/it]
ChatCompletion(id='chatcmpl-9MyMG7HWlTwz0hENgTZYRcPqClm6a', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["wrong account", "transaction error", "correct transaction mistake"]', role='assistant', function_call=None, tool_calls=None))], created=1715262260, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["wrong account", "transaction error", "correct transaction mistake"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The transfer I just made needs to be cancelled right now. It was my mistake. Please help me cancel it before it goes through!"

Keyphrases:
707it [17:13,  1.46s/it]
ChatCompletion(id='chatcmpl-9MyMIm8YN3Mu8zw1qMs7LyO5nBX8L', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["urgent transfer cancellation", "cancel immediate transfer", "reverse transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262262, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=245, total_tokens=259))
["urgent transfer cancellation", "cancel immediate transfer", "reverse transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to go back on what I did this morning"

Keyphrases:
708it [17:14,  1.48s/it]
ChatCompletion(id='chatcmpl-9MyMJraGGvPYCO8ipHA86TgU7dJqA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["undo actions", "reverse transaction", "transaction reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262263, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["undo actions", "reverse transaction", "transaction reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can a transaction be cancelled?"

Keyphrases:
709it [17:16,  1.55s/it]
ChatCompletion(id='chatcmpl-9MyMLFNas9aa5jbs3APJQarw9axWS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transaction", "transaction reversal", "undo transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262265, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["cancel transaction", "transaction reversal", "undo transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do i cancel my transaction?"

Keyphrases:
710it [17:17,  1.49s/it]
ChatCompletion(id='chatcmpl-9MyMMBy8xxqIOc1TQHvyHcbAJ9iv9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transaction", "transaction reversal", "stop payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715262266, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["cancel transaction", "transaction reversal", "stop payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transaction needs to be canceled."

Keyphrases:
711it [17:19,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyMOvhUyRWqIHJZJY0zP5Pe4etvv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transaction", "transaction reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262268, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=8, prompt_tokens=225, total_tokens=233))
["cancel transaction", "transaction reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to make an immediate cancellation related to a transfer. This was a mistake. Please assist quickly so this does not actually go through."

Keyphrases:
712it [17:21,  1.58s/it]
ChatCompletion(id='chatcmpl-9MyMPo3SwCiaCnDakPccW9VIwQq3i', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["urgent cancellation", "cancel transfer", "immediate assistance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262269, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=246, total_tokens=259))
["urgent cancellation", "cancel transfer", "immediate assistance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a mistake and need to cancel a transaction"

Keyphrases:
713it [17:22,  1.46s/it]
ChatCompletion(id='chatcmpl-9MyMRFLRU6qSpkVT2gVqJipt29Gtt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transaction", "transaction error", "reverse transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262271, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["cancel transaction", "transaction error", "reverse transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made an error in payment yesterday and I need it fixed asap because it's for my rent tomorrow."

Keyphrases:
714it [17:23,  1.43s/it]
ChatCompletion(id='chatcmpl-9MyMS6wA4NRMnrd3Zgj4T9VKwA0LY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment error", "urgent correction", "rent payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262272, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=240, total_tokens=253))
["payment error", "urgent correction", "rent payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Cancel my last transfer"

Keyphrases:
715it [17:26,  1.83s/it]
ChatCompletion(id='chatcmpl-9MyMUmzhrADBvOPPCIRAiMGtENr44', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transfer", "revoke transaction", "undo last transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262274, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=223, total_tokens=237))
["cancel transfer", "revoke transaction", "undo last transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My recent transfer needs to be cancelled immediately; it was a mistake, please can you cancel it before it goes through?"

Keyphrases:
716it [17:27,  1.68s/it]
ChatCompletion(id='chatcmpl-9MyMWi380SH9UDP3LptZifTRe9BgH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transfer", "emergency cancellation", "stop pending transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262276, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=242, total_tokens=255))
["cancel transfer", "emergency cancellation", "stop pending transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need help cancelling a transaction."

Keyphrases:
717it [17:29,  1.58s/it]
ChatCompletion(id='chatcmpl-9MyMY8E6OFFRADGGMotUPezJ7T7PA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transaction", "transaction reversal", "stop payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715262278, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["cancel transaction", "transaction reversal", "stop payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't want the transaction to go through now"

Keyphrases:
718it [17:30,  1.53s/it]
ChatCompletion(id='chatcmpl-9MyMZNCvxOWJcHcaJo34wBof4RtlU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["delay transaction", "postpone transaction", "cancel pending transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262279, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["delay transaction", "postpone transaction", "cancel pending transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I change the amount I made on a payment that I made to the payment is correct."

Keyphrases:
719it [17:31,  1.50s/it]
ChatCompletion(id='chatcmpl-9MyMaIKCb3ubxnEHOFK3k8Cw5pUTO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["modify payment amount", "correct payment value", "adjust payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715262280, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=237, total_tokens=251))
["modify payment amount", "correct payment value", "adjust payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please help me!  I need to cancel a transaction."

Keyphrases:
720it [17:34,  1.86s/it]
ChatCompletion(id='chatcmpl-9MyMcheoNRBzp2jQSoKMTVIu4hTx1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel transaction", "transaction reversal", "stop payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715262282, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["cancel transaction", "transaction reversal", "stop payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "can you limit my top up?"

Keyphrases:
721it [17:35,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyMeppUycFVIDNyw1eUT7rFCY4Sn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up limit", "set spending limit", "limit transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262284, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["top up limit", "set spending limit", "limit transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Am I free to top-up as much as I want?"

Keyphrases:
722it [17:37,  1.52s/it]
ChatCompletion(id='chatcmpl-9MyMgFxz8Bol8g8KPsH64hCIok1aP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limits", "account restrictions", "funding limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715262286, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["top-up limits", "account restrictions", "funding limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a top up limit for my account?"

Keyphrases:
723it [17:38,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyMhQgyEGIbF7bQUEa6EjK6YbdgG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up limit", "account limit", "funding restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715262287, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top up limit", "account limit", "funding restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the limit to top up?"

Keyphrases:
724it [17:39,  1.49s/it]
ChatCompletion(id='chatcmpl-9MyMiPG8mCG9phJxbhdpAnUOadcZX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up limit", "account limit", "funding limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262288, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["top up limit", "account limit", "funding limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much money can i top up?"

Keyphrases:
725it [17:41,  1.63s/it]
ChatCompletion(id='chatcmpl-9MyMkcmTA6HqJOEYIkKyo4kSu2oHm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up limit", "maximum top up", "funds addition limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262290, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["top up limit", "maximum top up", "funds addition limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the restrictions to top-offs?"

Keyphrases:
726it [17:44,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyMmjDavutLtyjAcz6t8t0eMI6ki', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-off limits", "account reload restrictions", "funding restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715262292, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["top-off limits", "account reload restrictions", "funding restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are the top-ups limited?"

Keyphrases:
727it [17:45,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyMoonCPfNPCNcQchtocFDgAYtsG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limits", "account limitations", "funding restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715262294, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["top-up limits", "account limitations", "funding restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what is the top up limit"

Keyphrases:
728it [17:47,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyMqFzVAwv0YvVaq38TOJegSj3iU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up limit", "account limits", "maximum deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262296, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["top up limit", "account limits", "maximum deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to find out what is the limit for top-ups."

Keyphrases:
729it [17:49,  1.95s/it]
ChatCompletion(id='chatcmpl-9MyMrzlWZauxFPn3PyQijbv4QFLLZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "account limits", "transaction limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262297, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["top-up limit", "account limits", "transaction limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you have a limit to top ups?"

Keyphrases:
730it [17:52,  2.20s/it]
ChatCompletion(id='chatcmpl-9MyMuuYlqwY5uVCGGmAJ3zOrnMKNW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up limit", "account reload limit", "maximum deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262300, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["top up limit", "account reload limit", "maximum deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is maximum top up?"

Keyphrases:
731it [17:55,  2.37s/it]
ChatCompletion(id='chatcmpl-9MyMw7oro4wZYufHPRbZcVExWXmls', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["maximum top up", "top up limit", "account limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262302, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["maximum top up", "top up limit", "account limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I tell what the limit is to top-ups?"

Keyphrases:
732it [17:57,  2.23s/it]
ChatCompletion(id='chatcmpl-9MyMz0DpxLcJpo435BJuoGR5EDQOi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "account limit", "maximum top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262305, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["top-up limit", "account limit", "maximum top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a limit to top-up amounts?"

Keyphrases:
733it [17:59,  2.17s/it]
ChatCompletion(id='chatcmpl-9MyN1RkcEt8CVVrfIqg3mEAZvZopF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "maximum top-up", "funding restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715262307, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["top-up limit", "maximum top-up", "funding restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there any limit to the amount I can add to a card at a time?"

Keyphrases:
734it [18:00,  2.00s/it]
ChatCompletion(id='chatcmpl-9MyN37iRYKdCLRFtQn7uQgZu9rReu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund limit", "card top-up limit", "maximum deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262309, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["fund limit", "card top-up limit", "maximum deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to know if there is a maximum I can top up."

Keyphrases:
735it [18:02,  1.91s/it]
ChatCompletion(id='chatcmpl-9MyN5mVUMupkIZJkPg5y0OtlQrh6z', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up limit", "maximum top up amount", "account reload limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262311, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["top up limit", "maximum top up amount", "account reload limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the limit to a top-up?"

Keyphrases:
736it [18:04,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyN6fJWH392lsEvKPo8N4cU9FUge', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "account limit", "funding restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715262312, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["top-up limit", "account limit", "funding restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Tell me if there are any top-up limits?"

Keyphrases:
737it [18:05,  1.54s/it]
ChatCompletion(id='chatcmpl-9MyN86m3YxA3Il9NFnkWBGmsDtOE5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limits", "account recharge limit", "maximum deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262314, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top-up limits", "account recharge limit", "maximum deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I top-up my limit?"

Keyphrases:
738it [18:06,  1.49s/it]
ChatCompletion(id='chatcmpl-9MyN9niegi9Fwi19VFLK79XANn5OJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["increase limit", "credit limit request", "limit top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262315, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["increase limit", "credit limit request", "limit top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a limit to top-ups?"

Keyphrases:
739it [18:07,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyNA3VMYd28hVc4PKOUlAoQ75YLz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "account limit", "deposit cap"]', role='assistant', function_call=None, tool_calls=None))], created=1715262316, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["top-up limit", "account limit", "deposit cap"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I top-up as much as I want?"

Keyphrases:
740it [18:09,  1.39s/it]
ChatCompletion(id='chatcmpl-9MyNCVxZnA0FvYmeGbS37FlHbHQDh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limits", "maximum top-up", "funding limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715262318, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["top-up limits", "maximum top-up", "funding limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me the limits for top ups?"

Keyphrases:
741it [18:10,  1.32s/it]
ChatCompletion(id='chatcmpl-9MyNDBzAoAooPqgtI8b9cJOecfp3s', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up limits", "account limits", "funding limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715262319, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top up limits", "account limits", "funding limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When I top up what are the amoutn limits."

Keyphrases:
742it [18:12,  1.69s/it]
ChatCompletion(id='chatcmpl-9MyNEG9lzsZnda3MOcaP7P8YnhSyu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up limits", "transaction limits", "deposit limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715262320, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["top up limits", "transaction limits", "deposit limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a limit on top-ups?"

Keyphrases:
743it [18:14,  1.58s/it]
ChatCompletion(id='chatcmpl-9MyNHBjdHPGFPswluvygchbiTk7XC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "account limit", "funding restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715262323, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["top-up limit", "account limit", "funding restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the top-ups limit?"

Keyphrases:
744it [18:15,  1.59s/it]
ChatCompletion(id='chatcmpl-9MyNIkTMADzJDgNXDlJjfPzqZufWv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limits", "account limits", "funding limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715262324, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["top-up limits", "account limits", "funding limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there limits to top-ups?"

Keyphrases:
745it [18:17,  1.59s/it]
ChatCompletion(id='chatcmpl-9MyNJYDugLNVQt4r14iFHvDwMeIqX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limits", "account refill restrictions", "maximum top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262325, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["top-up limits", "account refill restrictions", "maximum top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a maximum amount of top-ups?"

Keyphrases:
746it [18:18,  1.50s/it]
ChatCompletion(id='chatcmpl-9MyNLEtrJFEpfgWcvAdKhrWn2eC48', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "maximum top-up", "account limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715262327, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["top-up limit", "maximum top-up", "account limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you have a top-up limit?"

Keyphrases:
747it [18:19,  1.41s/it]
ChatCompletion(id='chatcmpl-9MyNMrcXJ6bEUzWsFFi4liOAzKf4S', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "account limit", "maximum deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262328, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["top-up limit", "account limit", "maximum deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What's the top up limit?"

Keyphrases:
748it [18:21,  1.38s/it]
ChatCompletion(id='chatcmpl-9MyNN9xt3u0PVhjQSEXH3bkk8EITV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up limit", "account limit", "maximum deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262329, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["top up limit", "account limit", "maximum deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the limit to top-up?"

Keyphrases:
749it [18:22,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyNPgEsI71hWo643jajn5NA7s0tn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "account reload limit", "maximum top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262331, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["top-up limit", "account reload limit", "maximum top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much can I top-up to my card at a time?"

Keyphrases:
750it [18:24,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyNQmaAkBnYv9XFmGVRcnakfZTwo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card top-up limit", "maximum top-up amount", "top-up restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715262332, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["card top-up limit", "maximum top-up amount", "top-up restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how much can i top up?"

Keyphrases:
751it [18:25,  1.51s/it]
ChatCompletion(id='chatcmpl-9MyNSwvh0P192nnqw5bLSavr0iRKU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up limit", "maximum top-up", "account reload limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262334, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["top up limit", "maximum top-up", "account reload limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what is the most i can top up?"

Keyphrases:
752it [18:27,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyNUcDvSGMExzFN2ZEDAVwtBs11Y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up limit", "maximum top-up", "funding limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715262336, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["top up limit", "maximum top-up", "funding limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a limit to how high I can top-up?"

Keyphrases:
753it [18:28,  1.50s/it]
ChatCompletion(id='chatcmpl-9MyNVGrVdgd1SbtwxF5yaH5VfFI4J', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "account recharge limit", "maximum top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262337, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["top-up limit", "account recharge limit", "maximum top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there an amount limit to my top-up?"

Keyphrases:
754it [18:30,  1.49s/it]
ChatCompletion(id='chatcmpl-9MyNXj5u5NmXdkdQ0GyPA6jsnMXfM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "maximum top-up amount", "funding limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262339, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["top-up limit", "maximum top-up amount", "funding limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a limit for top-ups?"

Keyphrases:
755it [18:31,  1.54s/it]
ChatCompletion(id='chatcmpl-9MyNYq54YNcFUF3bneVnFFEq76piF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "account recharge limit", "maximum top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262340, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["top-up limit", "account recharge limit", "maximum top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a maximum i can top up?"

Keyphrases:
756it [18:33,  1.48s/it]
ChatCompletion(id='chatcmpl-9MyNaIDrQl7w484ZyYOFwqxEu56Hg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up limit", "maximum top up amount", "account recharge limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262342, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["top up limit", "maximum top up amount", "account recharge limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I tell if there is a top-up limit?"

Keyphrases:
757it [18:34,  1.38s/it]
ChatCompletion(id='chatcmpl-9MyNbeJHeXDPfKi2ilMR03RMyFTtX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limit", "account limit", "maximum deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262343, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["top-up limit", "account limit", "maximum deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you have any restrictions to my top-up?"

Keyphrases:
758it [18:35,  1.33s/it]
ChatCompletion(id='chatcmpl-9MyNcoJYhe1msOScbEUVXOPNUX0Bh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up restrictions", "account limitations", "funding limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715262344, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top-up restrictions", "account limitations", "funding limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "As for limits are top ups included?"

Keyphrases:
759it [18:36,  1.33s/it]
ChatCompletion(id='chatcmpl-9MyNdoK2cWwjQoHtUJPYRQsPqjeJt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account limits", "top up limits", "inclusion in limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715262345, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["account limits", "top up limits", "inclusion in limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the top-up limits?"

Keyphrases:
760it [18:41,  2.16s/it]
ChatCompletion(id='chatcmpl-9MyNfQyAeaF3byeq0w3wCD65gZzbi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up limits", "account limits", "deposit limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715262347, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["top-up limits", "account limits", "deposit limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't know if this is an issue with the ATM or my account, but I just tried withdrawing 30 pounds from the ATM I'm at now and it only gave me 10. Is this a glitch or what exactly is going on?"

Keyphrases:
761it [18:43,  2.17s/it]
ChatCompletion(id='chatcmpl-9MyNjOXDTIRaolzGQYWD5GdfTBVqD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "incorrect withdrawal amount", "withdrawal problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262351, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=268, total_tokens=284))
["ATM withdrawal issue", "incorrect withdrawal amount", "withdrawal problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I didn't get all the cash I requested for at the ATM"

Keyphrases:
762it [18:45,  2.13s/it]
ChatCompletion(id='chatcmpl-9MyNlc8FzMuwR4Fbf3ksyNTOZGuNu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "incomplete cash withdrawal", "ATM cash discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715262353, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=232, total_tokens=250))
["ATM withdrawal issue", "incomplete cash withdrawal", "ATM cash discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How come the ATM gave me less cash than what I asked for?"

Keyphrases:
763it [18:47,  2.05s/it]
ChatCompletion(id='chatcmpl-9MyNnVV077VqgG1EAjNA6IVamXtZU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal error", "incorrect cash dispensed", "ATM error"]', role='assistant', function_call=None, tool_calls=None))], created=1715262355, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=232, total_tokens=249))
["ATM withdrawal error", "incorrect cash dispensed", "ATM error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I not get my cash back after I withdrew?"

Keyphrases:
764it [18:49,  2.20s/it]
ChatCompletion(id='chatcmpl-9MyNpKxftQ9trvj3i82vZJS3v3NV3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash back issue", "missing cash back", "withdrawal problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262357, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["cash back issue", "missing cash back", "withdrawal problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got less cash than the one I specified in the ATM"

Keyphrases:
765it [18:52,  2.43s/it]
ChatCompletion(id='chatcmpl-9MyNrNReYxaF14c1198KbhVXgfhnj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM discrepancy", "withdrawal error", "incorrect ATM amount"]', role='assistant', function_call=None, tool_calls=None))], created=1715262359, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["ATM discrepancy", "withdrawal error", "incorrect ATM amount"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The amount of cash I received was incorrect"

Keyphrases:
766it [18:54,  2.35s/it]
ChatCompletion(id='chatcmpl-9MyNu5vuhR0OgvfySeoAroIFKSxXZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect transaction", "wrong cash amount", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715262362, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["incorrect transaction", "wrong cash amount", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm at an ATM and withdrew 30 pounds and was only given 10. What should I do?"

Keyphrases:
767it [18:57,  2.45s/it]
ChatCompletion(id='chatcmpl-9MyNyx4yv2gUfALUKDRVRRGhEU4Lm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "incorrect withdrawal amount", "withdrawal discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715262366, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=240, total_tokens=255))
["ATM issue", "incorrect withdrawal amount", "withdrawal discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM gave me the wrong amount of cash today when I went to withdraw. The app says it was more."

Keyphrases:
768it [18:59,  2.20s/it]
ChatCompletion(id='chatcmpl-9MyNzjHp2LracgIgWga9LVexFfJL2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM error", "incorrect withdrawal amount", "wrong cash dispensed"]', role='assistant', function_call=None, tool_calls=None))], created=1715262367, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=241, total_tokens=257))
["ATM error", "incorrect withdrawal amount", "wrong cash dispensed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The amount of cash I received was different than what I requested."

Keyphrases:
769it [19:01,  2.22s/it]
ChatCompletion(id='chatcmpl-9MyO1jRhsqPdFVlBboY0wiIA2AqAx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect cash amount", "cash withdrawal discrepancy", "ATM withdrawal issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262369, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["incorrect cash amount", "cash withdrawal discrepancy", "ATM withdrawal issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hi. I just withdrew cash from an ATM and received the wrong amount. However, my app shows the correct amount I withdrew. How do I get the rest of the cash?"

Keyphrases:
770it [19:02,  2.01s/it]
ChatCompletion(id='chatcmpl-9MyO3zWvqlTUuNiHv6Ix4Q02NbISU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "incorrect ATM withdrawal", "report ATM discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715262371, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=254, total_tokens=270))
["ATM withdrawal issue", "incorrect ATM withdrawal", "report ATM discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The wrong amount of cash came out of the ATM today when I went to withdraw. When I looked at the app, it was showing it was much more."

Keyphrases:
771it [19:04,  1.86s/it]
ChatCompletion(id='chatcmpl-9MyO5ShHDHKaroCEdwOkW3UGlUVX2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM discrepancy", "incorrect withdrawal amount", "ATM overcharge"]', role='assistant', function_call=None, tool_calls=None))], created=1715262373, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=250, total_tokens=266))
["ATM discrepancy", "incorrect withdrawal amount", "ATM overcharge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I did not get as much cash as I requested at the ATM."

Keyphrases:
772it [19:06,  1.94s/it]
ChatCompletion(id='chatcmpl-9MyO6ppWf1i6hWGOP0tHxaE2Qh9mq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM cash discrepancy", "incorrect withdrawal amount", "ATM withdrawal problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262374, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=232, total_tokens=249))
["ATM cash discrepancy", "incorrect withdrawal amount", "ATM withdrawal problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I request cash back? The ATM just gave me the wrong amount, the app shows the amount that I've been actually charged though..."

Keyphrases:
773it [19:07,  1.80s/it]
ChatCompletion(id='chatcmpl-9MyO8B5sj2STFIKPRy2unusCF2J6r', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash back request", "ATM error", "incorrect ATM withdrawal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262376, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=247, total_tokens=262))
["cash back request", "ATM error", "incorrect ATM withdrawal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is the money I pushed it's on my mobile app as being withdrawn."

Keyphrases:
774it [19:09,  1.68s/it]
ChatCompletion(id='chatcmpl-9MyOAtWVXEkdzPLBk2UxRMoMiExdg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["mobile app withdrawal", "withdrawal status", "money tracking"]', role='assistant', function_call=None, tool_calls=None))], created=1715262378, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["mobile app withdrawal", "withdrawal status", "money tracking"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I not get all the cash I asked for?"

Keyphrases:
775it [19:10,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyOBZ9vxFjQGFbmt2KPCxfpMIfWB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal issue", "incomplete cash withdrawal", "ATM issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262379, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["cash withdrawal issue", "incomplete cash withdrawal", "ATM issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My cash withdrawal was partly declined"

Keyphrases:
776it [19:12,  1.53s/it]
ChatCompletion(id='chatcmpl-9MyODve2E2HcTZv1KyUJcqcOsN7yT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["partial withdrawal", "withdrawal issue", "declined transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262381, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["partial withdrawal", "withdrawal issue", "declined transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I only get $20 when I tried to get $100"

Keyphrases:
777it [19:13,  1.49s/it]
ChatCompletion(id='chatcmpl-9MyOE5GoBX9W8O8wmvjtsePt12RD1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect withdrawal amount", "ATM withdrawal issue", "partial withdrawal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262382, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["incorrect withdrawal amount", "ATM withdrawal issue", "partial withdrawal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have withdrawn cash from ATM but i received the wrong amount. I want cash back as in app its showing actual amount which i got. Please help me in this."

Keyphrases:
778it [19:15,  1.56s/it]
ChatCompletion(id='chatcmpl-9MyOFfU4L72AeqeVCMUiHARc7f7Yl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect ATM withdrawal", "ATM discrepancy", "wrong cash amount"]', role='assistant', function_call=None, tool_calls=None))], created=1715262383, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=252, total_tokens=267))
["incorrect ATM withdrawal", "ATM discrepancy", "wrong cash amount"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I went to withdraw some cash earlier today, but seems the ATM gave me the wrong amount of cash! The amount showing up in the app is a lot more"

Keyphrases:
779it [19:17,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyOHwxTgOijhfNc55pbwWSRQ9QOg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "incorrect withdrawal amount", "ATM discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715262385, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=251, total_tokens=267))
["ATM withdrawal issue", "incorrect withdrawal amount", "ATM discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to get $100 but I just got $20"

Keyphrases:
780it [19:18,  1.56s/it]
ChatCompletion(id='chatcmpl-9MyOJUhD1wiFUdNcU3KuRMIek6Xge', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect withdrawal amount", "ATM issue", "dispensing error"]', role='assistant', function_call=None, tool_calls=None))], created=1715262387, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["incorrect withdrawal amount", "ATM issue", "dispensing error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have not received the amount of cash i was supposed to."

Keyphrases:
781it [19:19,  1.41s/it]
ChatCompletion(id='chatcmpl-9MyOKgzBrmNye5CklnG2jSLhzfxeB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing funds", "cash not received", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262388, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["missing funds", "cash not received", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I asked for $100 cash but only got $20?"

Keyphrases:
782it [19:20,  1.41s/it]
ChatCompletion(id='chatcmpl-9MyOLqqgoay5tqrOysnOmRSkeSwaC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect cash withdrawal", "ATM withdrawal issue", "cash dispensing error"]', role='assistant', function_call=None, tool_calls=None))], created=1715262389, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["incorrect cash withdrawal", "ATM withdrawal issue", "cash dispensing error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is the money that I asked for? I asked for more than I got!"

Keyphrases:
783it [19:22,  1.50s/it]
ChatCompletion(id='chatcmpl-9MyONL1jMhqxloBCcc6iIfJtBHg8H', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect amount", "funds discrepancy", "requested funds error"]', role='assistant', function_call=None, tool_calls=None))], created=1715262391, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["incorrect amount", "funds discrepancy", "requested funds error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I withdrew money but the full amount wasn't dispensed."

Keyphrases:
784it [19:24,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyOOSrzTlnzQYDMt887UlQ4lDMrU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "incomplete withdrawal", "dispensing error"]', role='assistant', function_call=None, tool_calls=None))], created=1715262392, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["ATM issue", "incomplete withdrawal", "dispensing error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Something went wrong with my withdrawal. The amount of money isn't right."

Keyphrases:
785it [19:25,  1.41s/it]
ChatCompletion(id='chatcmpl-9MyOQ30rq5Wc79wrFIstyWSDzYwRE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal issue", "incorrect withdrawal amount", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715262394, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["withdrawal issue", "incorrect withdrawal amount", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have got out the wrong amount from an ATM. Please tell me the process to get the cash back as in app its showing the amount i have been actually received."

Keyphrases:
786it [19:28,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyORTN2ojvWvIu8GdBwRMpktJu6N', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM discrepancy", "incorrect withdrawal amount", "cash back process"]', role='assistant', function_call=None, tool_calls=None))], created=1715262395, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=252, total_tokens=267))
["ATM discrepancy", "incorrect withdrawal amount", "cash back process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I asked for 100 but only got 20."

Keyphrases:
787it [19:29,  1.64s/it]
ChatCompletion(id='chatcmpl-9MyOUg3JRB3LBQexkGj2yPzDerkYG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect amount", "transaction error", "funds discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715262398, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["incorrect amount", "transaction error", "funds discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I didn't receive the right amount of cash back"

Keyphrases:
788it [19:30,  1.54s/it]
ChatCompletion(id='chatcmpl-9MyOV2lZt2y2Ok7GMwcmPL4ExHOB7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect cash back", "cash back error", "cash back discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715262399, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["incorrect cash back", "cash back error", "cash back discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM gave me less cash than I requested"

Keyphrases:
789it [19:32,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyOWRkIiCv9HzRc6kF8tk6HhRFph', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM discrepancy", "cash withdrawal issue", "incorrect ATM dispense"]', role='assistant', function_call=None, tool_calls=None))], created=1715262400, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["ATM discrepancy", "cash withdrawal issue", "incorrect ATM dispense"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I didn't get as much cash as I asked for from the ATM, why?"

Keyphrases:
790it [19:33,  1.56s/it]
ChatCompletion(id='chatcmpl-9MyOYRPeMGw3a6IEgk7amaEhyXdh0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM discrepancy", "incorrect withdrawal amount", "ATM cash error"]', role='assistant', function_call=None, tool_calls=None))], created=1715262402, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=235, total_tokens=251))
["ATM discrepancy", "incorrect withdrawal amount", "ATM cash error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do if the ATM didn't give me the correct amount I withdrew? I pulled out 30 pounds and the ATM gave me 10 pounds."

Keyphrases:
791it [19:35,  1.64s/it]
ChatCompletion(id='chatcmpl-9MyOaEClJqaFOFEfVt4lmMKse7ihj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM error", "incorrect withdrawal amount", "discrepancy in ATM withdrawal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262404, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=19, prompt_tokens=250, total_tokens=269))
["ATM error", "incorrect withdrawal amount", "discrepancy in ATM withdrawal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to take out cash but the amount isn't right, so what do I do?"

Keyphrases:
792it [19:37,  1.72s/it]
ChatCompletion(id='chatcmpl-9MyOb4VcM5I4mNDEIj7E2e6MgClBh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect withdrawal amount", "cash withdrawal issue", "ATM issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262405, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=237, total_tokens=252))
["incorrect withdrawal amount", "cash withdrawal issue", "ATM issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I didn't receive all the cash I asked for"

Keyphrases:
793it [19:39,  1.72s/it]
ChatCompletion(id='chatcmpl-9MyOd7l19xqSYBKE7j8ZxQ9KjmmLC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal issue", "incomplete cash withdrawal", "ATM issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262407, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["cash withdrawal issue", "incomplete cash withdrawal", "ATM issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I just got $20 when I tried to get $100"

Keyphrases:
794it [19:41,  1.72s/it]
ChatCompletion(id='chatcmpl-9MyOfETSwzGF16OXUjEdMPG98qExA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect withdrawal amount", "ATM error", "withdrawal problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262409, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["incorrect withdrawal amount", "ATM error", "withdrawal problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The right amount of cash was not sent to me."

Keyphrases:
795it [19:42,  1.59s/it]
ChatCompletion(id='chatcmpl-9MyOh88odTxQ47xjbebjuIvOJhsHN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect transfer amount", "wrong cash amount sent", "transfer discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715262411, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["incorrect transfer amount", "wrong cash amount sent", "transfer discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM didn't give me the the withdraw amount requested."

Keyphrases:
796it [19:43,  1.54s/it]
ChatCompletion(id='chatcmpl-9MyOiB9LtOrdEx3tNjmsLnY8MhzoS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "incorrect withdrawal amount", "ATM transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715262412, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["ATM withdrawal issue", "incorrect withdrawal amount", "ATM transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I get less money than I asked for?"

Keyphrases:
797it [19:47,  2.08s/it]
ChatCompletion(id='chatcmpl-9MyOjxAE9Ym0lykjBJBh55l2Aiwbj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect transfer amount", "transfer discrepancy", "amount mismatch"]', role='assistant', function_call=None, tool_calls=None))], created=1715262413, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["incorrect transfer amount", "transfer discrepancy", "amount mismatch"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I didn't get the right amount at the ATM."

Keyphrases:
798it [19:49,  2.21s/it]
ChatCompletion(id='chatcmpl-9MyOnoM3ltNWq0RDkTe1Q0yhnsn2p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM discrepancy", "incorrect withdrawal amount", "ATM withdrawal error"]', role='assistant', function_call=None, tool_calls=None))], created=1715262417, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["ATM discrepancy", "incorrect withdrawal amount", "ATM withdrawal error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "did not receive correct cash upon withdrawal"

Keyphrases:
799it [19:51,  1.97s/it]
ChatCompletion(id='chatcmpl-9MyOp8t9T1iIGKn5QPynGKw0CixUC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect withdrawal amount", "ATM error", "cash discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715262419, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["incorrect withdrawal amount", "ATM error", "cash discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will declined funds I tried to withdraw be returned to me?"

Keyphrases:
800it [19:52,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyOrDmO5AsnmmQGym9HsnlWiThDc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["declined withdrawal", "funds return", "withdrawal issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715262421, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["declined withdrawal", "funds return", "withdrawal issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I payed with a card and was charged an extra fee"

Keyphrases:
801it [19:54,  1.97s/it]
ChatCompletion(id='chatcmpl-9MyOsZkbLzWD6Zh9F3wCB9BI2F0pY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra fee", "card payment fee", "unexpected charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715262422, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["extra fee", "card payment fee", "unexpected charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was charged a fee after using my card and I shouldn't have been."

Keyphrases:
802it [19:56,  1.91s/it]
ChatCompletion(id='chatcmpl-9MyOvVfGQxUkOmVYibCwexcWieRtV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unjustified fee", "fee dispute", "incorrect charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715262425, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["unjustified fee", "fee dispute", "incorrect charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a reason I was charged a fee for using my card as payment? I've never had an extra fee before."

Keyphrases:
803it [19:57,  1.73s/it]
ChatCompletion(id='chatcmpl-9MyOwMkHHqxZMV6udk2AfjK6Gzfz0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fee query", "unexpected charge", "payment fee explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715262426, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=243, total_tokens=257))
["card fee query", "unexpected charge", "payment fee explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I show another charge on my card from when I used it, why?"

Keyphrases:
804it [19:59,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyOygMnXvs6cfqlZei3hHpDl6AIT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized charge", "dispute transaction", "card security issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262428, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["unauthorized charge", "dispute transaction", "card security issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do I get charged additional fees on some payments, but not others?"

Keyphrases:
805it [20:00,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyP0tsWK4ywBc4DK78ZNPkEouaXu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional fees", "payment fees", "fee structure"]', role='assistant', function_call=None, tool_calls=None))], created=1715262430, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=233, total_tokens=245))
["additional fees", "payment fees", "fee structure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I used my card for a purchase and was charged a fee"

Keyphrases:
806it [20:02,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyP1ERMBYHbTobwZj5V3solDPVdF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fee", "transaction fee", "unexplained charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715262431, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["card fee", "transaction fee", "unexplained charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I charged for card payment?"

Keyphrases:
807it [20:04,  1.78s/it]
ChatCompletion(id='chatcmpl-9MyP2wawEUmg9jWTIMH5ET2HmFR6q', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment charge", "unexplained charges", "fee explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715262432, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["card payment charge", "unexplained charges", "fee explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is an unauthorized fee."

Keyphrases:
808it [20:06,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyP48QGiHP92slJ44XbNKitXWRWs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized charge", "dispute fee", "report fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715262434, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["unauthorized charge", "dispute fee", "report fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would appreciate that someone let me know when there is an extra charge for payments. I was checking the app earlier and saying a charge on one of my payments that was additional that no one made me aware of before."

Keyphrases:
809it [20:08,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyP68LcHGzZ7J3GpaFQrGMjxozqV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unexpected charges", "additional payment charges", "fee disclosure"]', role='assistant', function_call=None, tool_calls=None))], created=1715262436, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=262, total_tokens=275))
["unexpected charges", "additional payment charges", "fee disclosure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I charged an extra fee when paying with my card?"

Keyphrases:
810it [20:10,  2.00s/it]
ChatCompletion(id='chatcmpl-9MyP8SuzVY9dtWNZHLT8E61J6lYpZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra fee", "unexpected charges", "card payment fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715262438, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["extra fee", "unexpected charges", "card payment fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I have to pay extra because I paid with card?"

Keyphrases:
811it [20:12,  1.89s/it]
ChatCompletion(id='chatcmpl-9MyPAXZ12PIFHjxHlor45ALYkFbs2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment fee", "extra charge", "payment surcharge"]', role='assistant', function_call=None, tool_calls=None))], created=1715262440, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["card payment fee", "extra charge", "payment surcharge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why are there fees for card usage?"

Keyphrases:
812it [20:13,  1.77s/it]
ChatCompletion(id='chatcmpl-9MyPCiKV8TeCA6ayk9YyPwgYmPA64', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fees", "usage fees", "transaction charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262442, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["card fees", "usage fees", "transaction charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "im not sure what this charge is for"

Keyphrases:
813it [20:14,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyPDoL0KDUCtbyOejXMHzJBCXz31', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized charge", "query charge", "explain charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715262443, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["unrecognized charge", "query charge", "explain charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the fee charged with this card payment?"

Keyphrases:
814it [20:16,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyPFp0blCIJy5ecozVoC5ujHTjL0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment fee", "transaction cost", "payment charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262445, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["card payment fee", "transaction cost", "payment charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When would my card be charged an extra fee for a transaction?"

Keyphrases:
815it [20:18,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyPHXvYdtY9dzbKtIBuv9SNG6mSm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction fee", "extra charge", "card fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715262447, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["transaction fee", "extra charge", "card fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I have to pay more when I do it with my card?"

Keyphrases:
816it [20:19,  1.52s/it]
ChatCompletion(id='chatcmpl-9MyPIEdrlqwjcF0RVr0WNIt2TNRVs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fees", "extra charges", "payment issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715262448, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=233, total_tokens=245))
["card fees", "extra charges", "payment issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a card payment and a fee is showing up?"

Keyphrases:
817it [20:21,  1.53s/it]
ChatCompletion(id='chatcmpl-9MyPJ85LSXNugFGv5bugMMPOh7o2t', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment fee", "unexplained fee", "transaction charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715262449, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["card payment fee", "unexplained fee", "transaction charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have been charged a fee for paying with card"

Keyphrases:
818it [20:24,  1.97s/it]
ChatCompletion(id='chatcmpl-9MyPLHVLZxrwYKfzbGDOMMLvHvtvP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment fee", "transaction fee", "banking fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715262451, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["card payment fee", "transaction fee", "banking fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the fee on my card payment?"

Keyphrases:
819it [20:26,  2.08s/it]
ChatCompletion(id='chatcmpl-9MyPOz8NmiHAh6NTUrkXiSRpLqouX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment fee", "transaction cost", "service charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715262454, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["card payment fee", "transaction cost", "service charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why would I be charged a fee for card payment?"

Keyphrases:
820it [20:28,  2.19s/it]
ChatCompletion(id='chatcmpl-9MyPRNxbeJLGKeFDUuT2ZbmDDIl3a', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment fee", "fee query", "payment charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262457, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["card payment fee", "fee query", "payment charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will I always be charged a fee for using my card?"

Keyphrases:
821it [20:30,  2.00s/it]
ChatCompletion(id='chatcmpl-9MyPTmgaMfyfDxugHPnzNKe7KjxWK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card usage fee", "transaction fee", "fee policy"]', role='assistant', function_call=None, tool_calls=None))], created=1715262459, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["card usage fee", "transaction fee", "fee policy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I check somewhere if there will be a fee on my payment or not? Seems you are charging in some cases, what's the pattern there?"

Keyphrases:
822it [20:31,  1.83s/it]
ChatCompletion(id='chatcmpl-9MyPUlTVyTn4RztnAHRmiYYjVOMu3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment fee", "fee inquiry", "transaction charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262460, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=248, total_tokens=260))
["payment fee", "fee inquiry", "transaction charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Paying in card resulted in a fee"

Keyphrases:
823it [20:33,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyPWnOKCHVV2BQ3EJEaUnhHkBjQ1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment fee", "transaction fee", "additional charge on card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262462, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["card payment fee", "transaction fee", "additional charge on card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I paid with card and I think there was a fee applied."

Keyphrases:
824it [20:34,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyPX2r22wyrfop3ZKfGq7CBHziGj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment fee", "transaction fee", "fee inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715262463, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["card payment fee", "transaction fee", "fee inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "So what items  actually come  with  extra  fees"

Keyphrases:
825it [20:36,  1.59s/it]
ChatCompletion(id='chatcmpl-9MyPZeG4kNLXIXEHZdmRMboLn6mCh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional fees", "fee details", "extra charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262465, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["additional fees", "fee details", "extra charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I avoid getting charged a fee on my card?"

Keyphrases:
826it [20:37,  1.42s/it]
ChatCompletion(id='chatcmpl-9MyPaCgO46yzqJ42EKgf2QJOqo0tO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["avoid fees", "card fees", "fee waiver"]', role='assistant', function_call=None, tool_calls=None))], created=1715262466, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["avoid fees", "card fees", "fee waiver"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a fee when you pay with your card?"

Keyphrases:
827it [20:40,  2.01s/it]
ChatCompletion(id='chatcmpl-9MyPbtImvjlQmm4vPQGOC7e6PNZ2g', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment fee", "transaction cost", "payment fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715262467, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["card payment fee", "transaction cost", "payment fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have been charged with a fee for paying with my card."

Keyphrases:
828it [20:42,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyPfZ9tWvLQjf1ld662JVDOtEFsd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fee", "payment charge", "transaction cost"]', role='assistant', function_call=None, tool_calls=None))], created=1715262471, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["card fee", "payment charge", "transaction cost"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "For the first time I got a fee on my account. How do I know when you charge these fees?"

Keyphrases:
829it [20:44,  1.85s/it]
ChatCompletion(id='chatcmpl-9MyPg3crHKFOTOXjWkHPAa3Xe4t3O', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account fees", "fee explanation", "fee schedule"]', role='assistant', function_call=None, tool_calls=None))], created=1715262472, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=240, total_tokens=252))
["account fees", "fee explanation", "fee schedule"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone needs to make me aware when there are extra charges for payments. I happened to be looking at the app earlier and noticed a charge associated to a payment that was extra that no one made me aware of before at all."

Keyphrases:
830it [20:45,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyPiElXdOBUbPW8Y6KhkvfDIKvAO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra charges", "hidden fees", "undisclosed charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715262474, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=263, total_tokens=276))
["extra charges", "hidden fees", "undisclosed charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is using my card free?"

Keyphrases:
831it [20:46,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyPjJnfPcJfRmOVR0qiXy15pjpjz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fees", "card charges", "free card usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715262475, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["card fees", "card charges", "free card usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I charged an extra fee when using a card?"

Keyphrases:
832it [20:48,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyPlQYXqBDW719nlTp7SXkKOUSyT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra fee", "unexpected charges", "fee clarification"]', role='assistant', function_call=None, tool_calls=None))], created=1715262477, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["extra fee", "unexpected charges", "fee clarification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What fees apply when using a card?"

Keyphrases:
833it [20:50,  1.63s/it]
ChatCompletion(id='chatcmpl-9MyPmknib7Eo36mlyF4qcvrhWYSpJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fees", "transaction costs", "banking fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715262478, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card fees", "transaction costs", "banking fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do you charge for payments? Why aren't your charges clearly laid out in the agreement?"

Keyphrases:
834it [20:51,  1.55s/it]
ChatCompletion(id='chatcmpl-9MyPofsxJtK1IsTysL01Zpt4iTbQI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment charges", "hidden fees", "service fees transparency"]', role='assistant', function_call=None, tool_calls=None))], created=1715262480, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=237, total_tokens=250))
["payment charges", "hidden fees", "service fees transparency"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I charged a fee when I paid with card?"

Keyphrases:
835it [20:52,  1.48s/it]
ChatCompletion(id='chatcmpl-9MyPplf7Ou3ic1OjWrWlM1siMojLU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fee charge", "payment fee", "card payment charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715262481, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["fee charge", "payment fee", "card payment charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a fee on my account. Why?"

Keyphrases:
836it [20:54,  1.42s/it]
ChatCompletion(id='chatcmpl-9MyPr7gOeSxM4K9aXEwlj3Ctzfo5W', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account fee", "fee inquiry", "fee explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715262483, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["account fee", "fee inquiry", "fee explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do you charge fees on card payments?"

Keyphrases:
837it [20:56,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyPsRV6CriS67Yx0eRekxCuQ4u5H', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fees", "payment fees", "fee explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715262484, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["card fees", "payment fees", "fee explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was charged a fee for a card payment. Why?"

Keyphrases:
838it [20:57,  1.52s/it]
ChatCompletion(id='chatcmpl-9MyPuNOimdj9v71SJS3uBAM9OkK5w', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fee explanation", "card payment charge", "payment fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715262486, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["fee explanation", "card payment charge", "payment fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was a charged a fee for using the card?"

Keyphrases:
839it [20:58,  1.44s/it]
ChatCompletion(id='chatcmpl-9MyPvQdb87dG4Do72IP5UNVWOGpvH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fee", "transaction charge", "fee explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715262487, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["card fee", "transaction charge", "fee explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "They charged me for paying with my card."

Keyphrases:
840it [21:01,  1.78s/it]
ChatCompletion(id='chatcmpl-9MyPxgb86Pqk6kcDulRf7oTyHWM4k', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment charge", "unauthorized charge", "transaction fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715262489, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["card payment charge", "unauthorized charge", "transaction fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I completed an in country transfer a few days ago and was sure to check the account information several times since the transaction was completed, but the funds are still not available. What is the problem?"

Keyphrases:
841it [21:04,  2.30s/it]
ChatCompletion(id='chatcmpl-9MyPzp0Jxj9rcct40Yquksmelk7a3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["in-country transfer issue", "delayed transfer", "funds not available"]', role='assistant', function_call=None, tool_calls=None))], created=1715262491, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=257, total_tokens=274))
["in-country transfer issue", "delayed transfer", "funds not available"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My money transfer has not arrived."

Keyphrases:
842it [21:06,  2.00s/it]
ChatCompletion(id='chatcmpl-9MyQ3JTyUDT202xIffOH02aBA9QxE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "transfer not received", "delayed money transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262495, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["missing transfer", "transfer not received", "delayed money transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am still waiting for a transaction to be completed"

Keyphrases:
843it [21:07,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyQ4SrDvl7x3AXC30OWNYd50lPSX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transaction", "transaction status", "transaction delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715262496, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["pending transaction", "transaction status", "transaction delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a money transaction but the recipient can't see it"

Keyphrases:
844it [21:09,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyQ61xh918DeqqhbR1szziS9MZ2R', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transaction issue", "recipient not seeing transaction", "transaction visibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715262498, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["money transaction issue", "recipient not seeing transaction", "transaction visibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to send someone money but they haven't received it."

Keyphrases:
845it [21:11,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyQ7HWpznoSyNAdof2h8dxUVA6nD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer issues", "failed transaction", "unreceived funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715262499, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["money transfer issues", "failed transaction", "unreceived funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does it take for a transfer to get to a recipient?"

Keyphrases:
846it [21:12,  1.67s/it]
ChatCompletion(id='chatcmpl-9MyQ9I5OYVzuRX9qO7qQu2dKgVIjZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer time", "payment processing time", "funds transfer duration"]', role='assistant', function_call=None, tool_calls=None))], created=1715262501, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["transfer time", "payment processing time", "funds transfer duration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can the recipient see my money transaction?"

Keyphrases:
847it [21:13,  1.58s/it]
ChatCompletion(id='chatcmpl-9MyQATip6SsUrUl9RE1TxOsJnSqdx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money visibility", "transaction viewing", "recipient transaction access"]', role='assistant', function_call=None, tool_calls=None))], created=1715262502, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["money visibility", "transaction viewing", "recipient transaction access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I transferred money but the recipient says it has not arrived. Why would this be?"

Keyphrases:
848it [21:15,  1.48s/it]
ChatCompletion(id='chatcmpl-9MyQCJAiPjnsuuzSx9kspTGmid1EX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer issue", "recipient not received", "transfer not arrived"]', role='assistant', function_call=None, tool_calls=None))], created=1715262504, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=235, total_tokens=250))
["money transfer issue", "recipient not received", "transfer not arrived"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The transfer I did hasn't arrived"

Keyphrases:
849it [21:16,  1.37s/it]
ChatCompletion(id='chatcmpl-9MyQDO52VgkU1LI7PL2gBytuoD15K', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "transfer not received", "delayed transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262505, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["missing transfer", "transfer not received", "delayed transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how long do money transfers take?"

Keyphrases:
850it [21:17,  1.33s/it]
ChatCompletion(id='chatcmpl-9MyQE92rp6V1WXE5jtbPhIzD6i7lO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer duration", "money transfer time", "transaction processing time"]', role='assistant', function_call=None, tool_calls=None))], created=1715262506, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["transfer duration", "money transfer time", "transaction processing time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I transferred some money and it didint arrive"

Keyphrases:
851it [21:18,  1.30s/it]
ChatCompletion(id='chatcmpl-9MyQFdgbK2VmzUoUvqocUl8r5QJHT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "delayed transfer", "transfer status"]', role='assistant', function_call=None, tool_calls=None))], created=1715262507, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["missing transfer", "delayed transfer", "transfer status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is the transfer I started?"

Keyphrases:
852it [21:20,  1.46s/it]
ChatCompletion(id='chatcmpl-9MyQHgSiX29PMt4zVi7N78JJ1Ymhj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer status", "pending transfer", "locate transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262509, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["transfer status", "pending transfer", "locate transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "transaction failed?"

Keyphrases:
853it [21:23,  2.06s/it]
ChatCompletion(id='chatcmpl-9MyQIzymjqCqPZ8oRmaGxpk2wo7mX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction issue", "failed transaction", "payment failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715262510, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=221, total_tokens=233))
["transaction issue", "failed transaction", "payment failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I just finished sending money, but it's not logging on the recipient side."

Keyphrases:
854it [21:25,  1.87s/it]
ChatCompletion(id='chatcmpl-9MyQMMor9J7adum4UfnsEiWlNyag2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer issues", "transfer not received", "sending money failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715262514, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["money transfer issues", "transfer not received", "sending money failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I completed a money transaction but the recipient hasn't received it"

Keyphrases:
855it [21:29,  2.41s/it]
ChatCompletion(id='chatcmpl-9MyQOeWY7vQ6fnK36NrrkEMDAEMzh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transaction issue", "recipient not received", "transaction completion"]', role='assistant', function_call=None, tool_calls=None))], created=1715262516, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["money transaction issue", "recipient not received", "transaction completion"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The receipient doesn't see my money transfer."

Keyphrases:
856it [21:30,  2.08s/it]
ChatCompletion(id='chatcmpl-9MyQRNRo0cvzWZzBU5UwyFMy8plk7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer visibility", "recipient did not receive transfer", "transfer not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715262519, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["money transfer visibility", "recipient did not receive transfer", "transfer not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I transferred the rent payment for my new place a couple days ago but the landlord says it's not there yet, despite showing up as done on my side. I checked the account number I sent it to and it's definitely correct. Can you please verify if the transaction really went through or not?"

Keyphrases:
857it [21:31,  1.90s/it]
ChatCompletion(id='chatcmpl-9MyQSvwLM0JsOmGvaCyridT2NkPKg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer verification", "transaction status", "completed transfer inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715262520, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=278, total_tokens=291))
["transfer verification", "transaction status", "completed transfer inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to find out why my transfer didn't get there."

Keyphrases:
858it [21:33,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyQUUVBzOJu0l9m0k5rHYgnjJIxR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "transfer not received", "transfer issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262522, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["missing transfer", "transfer not received", "transfer issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've just moved address from a place in Durham to a place in Walton-On-The-Naze.  I have a new landlord at my new house and they haven't got my payment but I know I sent it on time, can you check they got it please?"

Keyphrases:
859it [21:34,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyQVQREe8lvUeyoemHjYSpu2frnC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment status", "landlord payment issue", "confirm payment receipt"]', role='assistant', function_call=None, tool_calls=None))], created=1715262523, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=272, total_tokens=287))
["payment status", "landlord payment issue", "confirm payment receipt"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I sent money.  They haven't received it."

Keyphrases:
860it [21:35,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyQWwqhBpuqgcKoNZvKUv9fkZkyU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer status", "transfer not received", "pending transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262524, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["money transfer status", "transfer not received", "pending transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hey, I need some help figuring out way my transfer is not complete yet. My Landlord hasn't got the money yet.She should have received it by now."

Keyphrases:
861it [21:37,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyQYX9aAVQ6fFdMwc4K80F0ZVLGT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer delay", "transfer not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715262526, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=251, total_tokens=264))
["pending transfer", "transfer delay", "transfer not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The day before yesterday, I performed a transfer which was within this country. It still hasn't gone through. Can you check on that? The account number is definitely correct, as I've checked and double checked."

Keyphrases:
862it [21:40,  2.10s/it]
ChatCompletion(id='chatcmpl-9MyQZ23TLYQdDrPprmWatjoBntB1s', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["domestic transfer status", "transfer delay", "pending transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262527, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=261, total_tokens=275))
["domestic transfer status", "transfer delay", "pending transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm having a problem with a money transfer.  I sent some money to a friend a couple of hours ago, and they haven't received it yet.  Why hasn't it gotten to them? How long do transfers need to go through?"

Keyphrases:
863it [21:42,  1.95s/it]
ChatCompletion(id='chatcmpl-9MyQcDUxP8HnVQqNIisnBAbPNyWJp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer issue", "transfer delay", "transaction time"]', role='assistant', function_call=None, tool_calls=None))], created=1715262530, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=268, total_tokens=281))
["money transfer issue", "transfer delay", "transaction time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I transferred some money but the receiver can't pick it up for some reason."

Keyphrases:
864it [21:43,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyQeYQd3KjMtvQEDUfQXER9A0pvN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "money transfer problem", "receiver cannot access funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715262532, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["transfer issue", "money transfer problem", "receiver cannot access funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is the transaction I made to a friend?"

Keyphrases:
865it [21:45,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyQgZKmCl1StYMy9HONWmKq5sKKz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction status", "missing transaction", "friend transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262534, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["transaction status", "missing transaction", "friend transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My friend still hasn't gotten a transaction I made."

Keyphrases:
866it [21:47,  1.84s/it]
ChatCompletion(id='chatcmpl-9MyQiEn1cMAZqDJfa8sfbM4sTeaqr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transaction", "transaction not received", "transfer status"]', role='assistant', function_call=None, tool_calls=None))], created=1715262536, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["pending transaction", "transaction not received", "transfer status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Im waiting for my transaction to go through."

Keyphrases:
867it [21:49,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyQjFMeoNTlT2BfCK039rctMLwau', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transaction", "transaction status", "transaction delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715262537, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["pending transaction", "transaction status", "transaction delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a transaction and it is taking a very long time to go through."

Keyphrases:
868it [21:50,  1.67s/it]
ChatCompletion(id='chatcmpl-9MyQlLhKs3ckDquWn8EY8KbpXEV9I', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction delay", "long processing time", "slow transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262539, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["transaction delay", "long processing time", "slow transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a reason why my transaction is taking so long?"

Keyphrases:
869it [21:51,  1.56s/it]
ChatCompletion(id='chatcmpl-9MyQmyzi29Tg27abwbVO5O9C9DYmk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction delay", "slow transaction", "long transaction time"]', role='assistant', function_call=None, tool_calls=None))], created=1715262540, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["transaction delay", "slow transaction", "long transaction time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long will it take for my transaction to be completed?"

Keyphrases:
870it [21:53,  1.49s/it]
ChatCompletion(id='chatcmpl-9MyQoAnjtX78f0JdrQcDDjmPDDthp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction time", "completion time", "transaction duration"]', role='assistant', function_call=None, tool_calls=None))], created=1715262542, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["transaction time", "completion time", "transaction duration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I sent some money and the receiver can't access it."

Keyphrases:
871it [21:56,  2.03s/it]
ChatCompletion(id='chatcmpl-9MyQp8Hd3reS0WmOIzcu3MoH1Wkye', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer issues", "receiver access problem", "transfer accessibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715262543, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["money transfer issues", "receiver access problem", "transfer accessibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I sent my friend some money a few hours ago but she has not received it yet. She really needs it. How long does this take?"

Keyphrases:
872it [21:57,  1.77s/it]
ChatCompletion(id='chatcmpl-9MyQsgcSL6JiS3B5QgOHMqpohmsRu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer delay", "transfer time", "pending transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262546, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=247, total_tokens=260))
["money transfer delay", "transfer time", "pending transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The person I sent money to hasn't gotten it yet!"

Keyphrases:
873it [21:59,  1.93s/it]
ChatCompletion(id='chatcmpl-9MyQuaVVWB2mCBWnVZ7k8C8tdA07V', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "delayed transfer", "transfer not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715262548, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["pending transfer", "delayed transfer", "transfer not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will my funds transfer?"

Keyphrases:
874it [22:05,  2.90s/it]
ChatCompletion(id='chatcmpl-9MyQwCh36dfG4Dlve0A4nnFcUJ2zU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer timing", "transfer schedule", "when transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262550, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["fund transfer timing", "transfer schedule", "when transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does it take for transfers to finish?  I sent funds to my pal, and she says that she has not gotten anything."

Keyphrases:
875it [22:06,  2.45s/it]
ChatCompletion(id='chatcmpl-9MyR19NvXOR76zHfxZ74QFM8VYcUm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer time", "transfer delay", "transfer completion time"]', role='assistant', function_call=None, tool_calls=None))], created=1715262555, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=246, total_tokens=260))
["fund transfer time", "transfer delay", "transfer completion time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long do transfers need to come through? I sent some money to a friend, she needs it urgently, but seems it's still not there yet after a couple hours."

Keyphrases:
876it [22:07,  2.17s/it]
ChatCompletion(id='chatcmpl-9MyR2ehZHBpp0TNy0ydo4SxDPDHxq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer delay", "transfer time", "urgent transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262556, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=253, total_tokens=265))
["transfer delay", "transfer time", "urgent transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long until my friend receives my transaction?"

Keyphrases:
877it [22:09,  1.93s/it]
ChatCompletion(id='chatcmpl-9MyR431pNP8Fn4k8gSPYlhLTNKsMi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction time", "money transfer duration", "transfer ETA"]', role='assistant', function_call=None, tool_calls=None))], created=1715262558, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["transaction time", "money transfer duration", "transfer ETA"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why hasn't my recipient received their money?"

Keyphrases:
878it [22:10,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyR58fjPYU0nb0oyyPj5uGOAzZjG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer status", "recipient not paid", "delayed transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262559, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["money transfer status", "recipient not paid", "delayed transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am still awaiting the completion of the transaction."

Keyphrases:
879it [22:12,  1.64s/it]
ChatCompletion(id='chatcmpl-9MyR7xcxOYBN2F0JQF6p8HxVXlNGx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transaction", "transaction status", "completion delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715262561, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["pending transaction", "transaction status", "completion delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I transferred some money but the recipient is having trouble withdrawing."

Keyphrases:
880it [22:13,  1.63s/it]
ChatCompletion(id='chatcmpl-9MyR8aWubPk7Goxiy5EGSwkKpJu5D', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issues", "withdrawal problems", "recipient cannot withdraw"]', role='assistant', function_call=None, tool_calls=None))], created=1715262562, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["transfer issues", "withdrawal problems", "recipient cannot withdraw"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "To add money to my account, what currencies can I use?"

Keyphrases:
881it [22:14,  1.48s/it]
ChatCompletion(id='chatcmpl-9MyR9mwKjty5nXxHkhHdRMIhptkQP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency support", "adding money", "account funding currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715262563, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["currency support", "adding money", "account funding currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need support options, I want to top my card"

Keyphrases:
882it [22:16,  1.44s/it]
ChatCompletion(id='chatcmpl-9MyRBSC8Hhug835OiQRpZAHtX4MFx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["support options", "card top-up", "customer support"]', role='assistant', function_call=None, tool_calls=None))], created=1715262565, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["support options", "card top-up", "customer support"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have 1 other US card.  Can you take that?"

Keyphrases:
883it [22:17,  1.54s/it]
ChatCompletion(id='chatcmpl-9MyRCwa2rtvsJYeMQQAewIGkjKFQh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["alternative payment method", "use different card", "other US card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262566, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["alternative payment method", "use different card", "other US card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the cards and currencies that are supported?"

Keyphrases:
884it [22:19,  1.46s/it]
ChatCompletion(id='chatcmpl-9MyRE8b75EUxqsFrB90oJgLlRaUY6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported cards", "supported currencies", "card types"]', role='assistant', function_call=None, tool_calls=None))], created=1715262568, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["supported cards", "supported currencies", "card types"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What currencies are accepted for adding money?"

Keyphrases:
885it [22:20,  1.53s/it]
ChatCompletion(id='chatcmpl-9MyRFhvujzJpMxWO9TRifaGr613MV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["accepted currencies", "currency support", "add money currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715262569, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["accepted currencies", "currency support", "add money currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What kind of currencies can I use to add money?"

Keyphrases:
886it [22:23,  1.71s/it]
ChatCompletion(id='chatcmpl-9MyRHwUnTYPFgVhsx62BGwlRcCi0K', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency options", "adding money currency", "supported currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715262571, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["currency options", "adding money currency", "supported currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I only own one other credit card from the USA. Will it be accepted?"

Keyphrases:
887it [22:24,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyRJlVPaXK6CiKpVGVBmkMGxJqzY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card acceptance", "card usability", "international card acceptance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262573, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["credit card acceptance", "card usability", "international card acceptance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I only have 1 other US card, can you take it?"

Keyphrases:
888it [22:25,  1.54s/it]
ChatCompletion(id='chatcmpl-9MyRKqBsErlcYxORGDi6dOtEDHgvS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["alternate payment method", "using another card", "secondary card option"]', role='assistant', function_call=None, tool_calls=None))], created=1715262574, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["alternate payment method", "using another card", "secondary card option"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use my American Express to add money to my account?"

Keyphrases:
889it [22:27,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyRMjHXIv8CAb04Hq8eKhZKwgJLq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["use credit card", "add money", "American Express"]', role='assistant', function_call=None, tool_calls=None))], created=1715262576, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["use credit card", "add money", "American Express"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "can you tell me what cards and currencies you take?"

Keyphrases:
890it [22:28,  1.43s/it]
ChatCompletion(id='chatcmpl-9MyRNlNi3fwsByVyug1aL0dhja8az', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["accepted cards", "supported currencies", "payment methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715262577, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["accepted cards", "supported currencies", "payment methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use American Express to add money into my account?"

Keyphrases:
891it [22:30,  1.65s/it]
ChatCompletion(id='chatcmpl-9MyROcYeZH2pXl8DTISZEL3DSdiAB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment methods", "add money", "using American Express"]', role='assistant', function_call=None, tool_calls=None))], created=1715262578, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["payment methods", "add money", "using American Express"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will you accept my other card from the U.S.?"

Keyphrases:
892it [22:32,  1.58s/it]
ChatCompletion(id='chatcmpl-9MyRQP0f7FVMdaj1RwCCM3mEkX4QU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "alternative payment methods", "US card acceptance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262580, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["card acceptance", "alternative payment methods", "US card acceptance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is accepted in regards to cards and currencies?"

Keyphrases:
893it [22:33,  1.64s/it]
ChatCompletion(id='chatcmpl-9MyRSBejlnI4IoSLkWfEgCAO9Yxku', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["accepted cards", "currency types", "payment methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715262582, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["accepted cards", "currency types", "payment methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will you accept my other card?"

Keyphrases:
894it [22:35,  1.77s/it]
ChatCompletion(id='chatcmpl-9MyRUTAEF7HX7o53hkWTwIVB8escz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "alternate payment method", "other card usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715262584, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["card acceptance", "alternate payment method", "other card usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to add money to my account through my American Express."

Keyphrases:
895it [22:38,  1.88s/it]
ChatCompletion(id='chatcmpl-9MyRWGx3Dv6vU1ZzrSfBOsrtEkRiQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["add funds", "account funding", "using American Express"]', role='assistant', function_call=None, tool_calls=None))], created=1715262586, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["add funds", "account funding", "using American Express"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Which cards do you guys support? I want to top up using my credit card."

Keyphrases:
896it [22:39,  1.86s/it]
ChatCompletion(id='chatcmpl-9MyRYlcO5YNvLdg3IJnObf0XMtUUi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported cards", "credit card compatibility", "card top-up options"]', role='assistant', function_call=None, tool_calls=None))], created=1715262588, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=235, total_tokens=250))
["supported cards", "credit card compatibility", "card top-up options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What credit cards are supported?"

Keyphrases:
897it [22:41,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyRaS5vqy7BJoZ7882LEzFLGChYN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported credit cards", "credit card compatibility", "available credit cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715262590, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["supported credit cards", "credit card compatibility", "available credit cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What cards and currencies do you support?"

Keyphrases:
898it [22:42,  1.71s/it]
ChatCompletion(id='chatcmpl-9MyRbudJTaGrYqc9NThqFl48RB3I1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported cards", "currency options", "card compatibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715262591, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["supported cards", "currency options", "card compatibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I transfer funds from my American Express into my account?"

Keyphrases:
899it [22:45,  2.02s/it]
ChatCompletion(id='chatcmpl-9MyRdxyHrBI6uQ3Dvhdq1dU3Pvbdm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer", "American Express to account", "bank transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715262593, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["fund transfer", "American Express to account", "bank transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I use American Express to add money to my account?"

Keyphrases:
900it [22:48,  2.12s/it]
ChatCompletion(id='chatcmpl-9MyRfjNAXvCQ3yHzsFodu84K65xHV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["American Express usage", "add money", "funding account with credit card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262595, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["American Express usage", "add money", "funding account with credit card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When adding money, what are the currencies you take?"

Keyphrases:
901it [22:49,  2.04s/it]
ChatCompletion(id='chatcmpl-9MyRiIcoLWEwkjM9hlc4akMDthlFH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency support", "adding money", "currency exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715262598, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["currency support", "adding money", "currency exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Which forms of currency are accepted?"

Keyphrases:
902it [22:51,  1.91s/it]
ChatCompletion(id='chatcmpl-9MyRkmRwWGCa3kOA1WPl2fOupJuwZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["accepted currencies", "payment methods", "currency types"]', role='assistant', function_call=None, tool_calls=None))], created=1715262600, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["accepted currencies", "payment methods", "currency types"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are US credit cards accepted?"

Keyphrases:
903it [23:05,  5.53s/it]
ChatCompletion(id='chatcmpl-9MyRly2BahvovNHT4OjyP8DV4v0lA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card acceptance", "US credit cards", "payment methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715262601, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["credit card acceptance", "US credit cards", "payment methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to add money but don't know what currencies you accept, can you tell me?"

Keyphrases:
904it [23:07,  4.40s/it]
ChatCompletion(id='chatcmpl-9MyRzhG26QNNgt5zfL5lRfsBCG9NC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["accepted currencies", "currency support", "add money currency query"]', role='assistant', function_call=None, tool_calls=None))], created=1715262615, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=237, total_tokens=251))
["accepted currencies", "currency support", "add money currency query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "why wouldn't you support american express? its a card i like and use often and i don't want to get a different one"

Keyphrases:
905it [23:09,  3.60s/it]
ChatCompletion(id='chatcmpl-9MyS1Dcp9BvhaWL1WCFHga13jlWwZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unsupported card type", "American Express support", "card compatibility issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715262617, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=245, total_tokens=260))
["unsupported card type", "American Express support", "card compatibility issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Tell me which cards and what currency is supported."

Keyphrases:
906it [23:10,  2.85s/it]
ChatCompletion(id='chatcmpl-9MyS3PdoRMlDZFSFFcZnEtemjSsFA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported cards", "currency options", "card types"]', role='assistant', function_call=None, tool_calls=None))], created=1715262619, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["supported cards", "currency options", "card types"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you support all cards and currencies?"

Keyphrases:
907it [23:11,  2.42s/it]
ChatCompletion(id='chatcmpl-9MyS4pSMwHrrYWLXLuhdc17kV6wjW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported cards", "currency support", "card compatibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715262620, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["supported cards", "currency support", "card compatibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Which credit or debit cards can I use to top up?"

Keyphrases:
908it [23:13,  2.13s/it]
ChatCompletion(id='chatcmpl-9MyS5VCeQnPfvHPsCzqV6A9AakKwL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card compatibility", "top up methods", "accepted cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715262621, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["card compatibility", "top up methods", "accepted cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What options do I have in regards to payment?"

Keyphrases:
909it [23:16,  2.57s/it]
ChatCompletion(id='chatcmpl-9MyS7AMLbVmKkGIYLyKoasLpyhEsR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment options", "payment methods", "payment alternatives"]', role='assistant', function_call=None, tool_calls=None))], created=1715262623, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["payment options", "payment methods", "payment alternatives"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I just have one other card from the US. Is that okay?"

Keyphrases:
910it [23:17,  2.19s/it]
ChatCompletion(id='chatcmpl-9MySAC0QZCamDRGyO6OnC6TxF7RZS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "US card usage", "international card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262626, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["card acceptance", "US card usage", "international card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are all the currencies and cards supported to use this?"

Keyphrases:
911it [23:19,  2.03s/it]
ChatCompletion(id='chatcmpl-9MySC3U48BckD3IXi1RL2kbEFBEUz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported currencies", "supported cards", "currency options", "card types"]', role='assistant', function_call=None, tool_calls=None))], created=1715262628, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["supported currencies", "supported cards", "currency options", "card types"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What cards to do you support to top up."

Keyphrases:
912it [23:21,  2.08s/it]
ChatCompletion(id='chatcmpl-9MySEQU6twf2fRtwx3E4NbJWqfYD8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported cards", "card compatibility", "top up options"]', role='assistant', function_call=None, tool_calls=None))], created=1715262630, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["supported cards", "card compatibility", "top up options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you accept other currencies besides US Dollars?"

Keyphrases:
913it [23:27,  3.21s/it]
ChatCompletion(id='chatcmpl-9MySGON1cesPkalaLZqvb84j8BOQD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency support", "multi-currency", "foreign currency acceptance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262632, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["currency support", "multi-currency", "foreign currency acceptance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use any currency to add money?"

Keyphrases:
914it [23:29,  2.73s/it]
ChatCompletion(id='chatcmpl-9MySLJZWamwyA39KK7jZlmyVUSy8z', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "add money", "multi-currency support"]', role='assistant', function_call=None, tool_calls=None))], created=1715262637, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["currency exchange", "add money", "multi-currency support"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is my currency okay to add money with?"

Keyphrases:
915it [23:30,  2.40s/it]
ChatCompletion(id='chatcmpl-9MySNmyaeF2LNuyb7OYmNUNCAcmXl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency compatibility", "add money", "fund addition"]', role='assistant', function_call=None, tool_calls=None))], created=1715262639, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["currency compatibility", "add money", "fund addition"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What cards and currencies will suffice?"

Keyphrases:
916it [23:32,  2.09s/it]
ChatCompletion(id='chatcmpl-9MySPbOvOjrPlQG74ZU4j2sNneYgB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["accepted cards", "supported currencies", "card compatibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715262641, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["accepted cards", "supported currencies", "card compatibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I use American Express to add funds to my account?"

Keyphrases:
917it [23:33,  1.90s/it]
ChatCompletion(id='chatcmpl-9MySQVQzePp7XXhI2ufDuNhfkOmZo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["funds addition", "American Express usage", "account top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262642, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["funds addition", "American Express usage", "account top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What cards and currencies are supported?"

Keyphrases:
918it [23:35,  1.89s/it]
ChatCompletion(id='chatcmpl-9MySR3Svoxkq5WAUMvdf4RiJcBNRE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported cards", "currency options", "card types"]', role='assistant', function_call=None, tool_calls=None))], created=1715262643, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["supported cards", "currency options", "card types"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What currencies or cards do you support for topping up?"

Keyphrases:
919it [23:38,  2.12s/it]
ChatCompletion(id='chatcmpl-9MySTEEjXdQ409xZSOtAJ6UeMnAr0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported currencies", "card top-up options", "currency support for topping up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262645, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["supported currencies", "card top-up options", "currency support for topping up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Which cards and currencies do you support?"

Keyphrases:
920it [23:39,  1.99s/it]
ChatCompletion(id='chatcmpl-9MySWXkIo3NixX9rkcRaQQLTMdH4J', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported cards", "supported currencies", "currency options"]', role='assistant', function_call=None, tool_calls=None))], created=1715262648, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["supported cards", "supported currencies", "currency options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I obtain my virtual card?"

Keyphrases:
921it [23:41,  1.82s/it]
ChatCompletion(id='chatcmpl-9MySYgviMr6hKNf5ZjsKuJiagYRYf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "access virtual card", "virtual card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262650, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["virtual card", "access virtual card", "virtual card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do you get a virtual card?"

Keyphrases:
922it [23:43,  1.82s/it]
ChatCompletion(id='chatcmpl-9MySZEW9OwUXlEVfPROdB8NHbAqQ9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card creation", "apply for virtual card", "obtaining virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262651, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=226, total_tokens=244))
["virtual card creation", "apply for virtual card", "obtaining virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I find a virtual card?"

Keyphrases:
923it [23:44,  1.77s/it]
ChatCompletion(id='chatcmpl-9MySbbhGHUGkhUSLaXqK3qceDW4ot', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "apply virtual card", "virtual card services"]', role='assistant', function_call=None, tool_calls=None))], created=1715262653, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["virtual card", "apply virtual card", "virtual card services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there an option to have a virtual card?"

Keyphrases:
924it [23:45,  1.60s/it]
ChatCompletion(id='chatcmpl-9MySdh3VsczYCMTmPk6gMlWcEB5sM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card availability", "digital card options", "e-card services"]', role='assistant', function_call=None, tool_calls=None))], created=1715262655, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["virtual card availability", "digital card options", "e-card services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I don't want a physical card can i get a virtual version?"

Keyphrases:
925it [23:47,  1.50s/it]
ChatCompletion(id='chatcmpl-9MySeop2Dpw37YtYrft7ZqyOk4ZdO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card option", "no physical card", "digital card alternative"]', role='assistant', function_call=None, tool_calls=None))], created=1715262656, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["virtual card option", "no physical card", "digital card alternative"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I requested a virtual card but it is not showing up. Why?"

Keyphrases:
926it [23:48,  1.57s/it]
ChatCompletion(id='chatcmpl-9MySfIZ2TK66liXppcys88zdzjUMj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issue", "virtual card not visible", "virtual card activation problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715262657, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=232, total_tokens=249))
["virtual card issue", "virtual card not visible", "virtual card activation problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me how to order a virtual card?"

Keyphrases:
927it [23:50,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyShVIqcazQIx9OMGjIRW4od6o05', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["order virtual card", "virtual card setup", "request virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262659, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["order virtual card", "virtual card setup", "request virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is the virtual card?"

Keyphrases:
928it [23:52,  1.58s/it]
ChatCompletion(id='chatcmpl-9MySjUf5dZufsGYUaXKIqERR25s85', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card location", "find virtual card", "access virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262661, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["virtual card location", "find virtual card", "access virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what is the virtual card"

Keyphrases:
929it [23:54,  1.80s/it]
ChatCompletion(id='chatcmpl-9MySkbOkDpfZsbIcoYiRFHfkCoe47', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card details", "what is virtual card", "digital card information"]', role='assistant', function_call=None, tool_calls=None))], created=1715262662, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=224, total_tokens=240))
["virtual card details", "what is virtual card", "digital card information"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how do i get a virtual card?"

Keyphrases:
930it [23:56,  1.88s/it]
ChatCompletion(id='chatcmpl-9MySm07CMhHmsvduZ91280PzJaOY6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issuance", "apply for virtual card", "digital card request"]', role='assistant', function_call=None, tool_calls=None))], created=1715262664, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["virtual card issuance", "apply for virtual card", "digital card request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I order a virtual card from?"

Keyphrases:
931it [23:58,  1.79s/it]
ChatCompletion(id='chatcmpl-9MySoWcc5Um7jxgBTRTaz2dKWWb4g', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["order virtual card", "virtual card issuance", "apply for virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262666, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["order virtual card", "virtual card issuance", "apply for virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I not get a virtual card yet?"

Keyphrases:
932it [23:59,  1.76s/it]
ChatCompletion(id='chatcmpl-9MySqyUuwuTPjfiWCVSgeRO70aroZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issuance", "delay in virtual card", "virtual card status"]', role='assistant', function_call=None, tool_calls=None))], created=1715262668, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["virtual card issuance", "delay in virtual card", "virtual card status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I order virtual cards?"

Keyphrases:
933it [24:02,  1.95s/it]
ChatCompletion(id='chatcmpl-9MySsTGDGv1X5BV0ukHOPg6oRg8Yg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["order virtual card", "virtual card issuance", "apply for virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262670, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["order virtual card", "virtual card issuance", "apply for virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me where I can order a virtual card?"

Keyphrases:
934it [24:03,  1.81s/it]
ChatCompletion(id='chatcmpl-9MySuJAjdayg50Ap9CXs6IqbTgQNM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card order", "order virtual card", "how to get virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262672, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["virtual card order", "order virtual card", "how to get virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible for me to get a virtual card?"

Keyphrases:
935it [24:05,  1.78s/it]
ChatCompletion(id='chatcmpl-9MySvGJCNYdiIshR1xHSNNiNDHu6M', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "digital card request", "apply for virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262673, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["virtual card", "digital card request", "apply for virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is this where I order a virtual card?"

Keyphrases:
936it [24:07,  1.74s/it]
ChatCompletion(id='chatcmpl-9MySxmaEXhkyjh7P3pm0ZqBgfCGZf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card order", "order virtual card", "digital card request"]', role='assistant', function_call=None, tool_calls=None))], created=1715262675, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["virtual card order", "order virtual card", "digital card request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the steps to getting a virtual card?"

Keyphrases:
937it [24:09,  1.88s/it]
ChatCompletion(id='chatcmpl-9MySzKSZGjPOF9P9PzjjKvrESG6kW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card application", "how to apply for virtual card", "virtual card steps"]', role='assistant', function_call=None, tool_calls=None))], created=1715262677, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=228, total_tokens=246))
["virtual card application", "how to apply for virtual card", "virtual card steps"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "help me obtain a virtual card"

Keyphrases:
938it [24:11,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyT1iw4Tz0dz5AHSSvZCAixqE4Sl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card request", "obtain virtual card", "virtual card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262679, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["virtual card request", "obtain virtual card", "virtual card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is the virtual card located?"

Keyphrases:
939it [24:14,  2.40s/it]
ChatCompletion(id='chatcmpl-9MyT3hl7viZmnsWD0qtcdwuV7WN1q', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card access", "locate virtual card", "virtual card usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715262681, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["virtual card access", "locate virtual card", "virtual card usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I order a virtual card?"

Keyphrases:
940it [24:17,  2.43s/it]
ChatCompletion(id='chatcmpl-9MyT7du017Ei5HfUVtlwZWBlgJadG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card order", "order virtual card", "apply for virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262685, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["virtual card order", "order virtual card", "apply for virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I obtain my virtual card?"

Keyphrases:
941it [24:20,  2.67s/it]
ChatCompletion(id='chatcmpl-9MyT9PJ8uGhoA1axJTyuVmGABfVvT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card obtainment", "how to get virtual card", "virtual card acquisition"]', role='assistant', function_call=None, tool_calls=None))], created=1715262687, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=226, total_tokens=244))
["virtual card obtainment", "how to get virtual card", "virtual card acquisition"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want a virtual card!"

Keyphrases:
942it [24:22,  2.32s/it]
ChatCompletion(id='chatcmpl-9MyTCuyOI3n1m5EBgv8STLO1Xs7mC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card request", "apply for virtual card", "virtual card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262690, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=224, total_tokens=240))
["virtual card request", "apply for virtual card", "virtual card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want one of those virtual cards!"

Keyphrases:
943it [24:23,  2.08s/it]
ChatCompletion(id='chatcmpl-9MyTEJAfOcTG553uZShqY38jeFpd3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card request", "apply for virtual card", "virtual card options"]', role='assistant', function_call=None, tool_calls=None))], created=1715262692, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["virtual card request", "apply for virtual card", "virtual card options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are virtual cards available to get?"

Keyphrases:
944it [24:25,  2.06s/it]
ChatCompletion(id='chatcmpl-9MyTFX4CDhbgdLHYI2FdyC1aau8l6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual cards availability", "access virtual cards", "virtual card services"]', role='assistant', function_call=None, tool_calls=None))], created=1715262693, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["virtual cards availability", "access virtual cards", "virtual card services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you help me sign up for a virtual card?"

Keyphrases:
945it [24:27,  1.94s/it]
ChatCompletion(id='chatcmpl-9MyTHblPrICUraeZ7qxUilSU7kxlZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card registration", "sign up for virtual card", "virtual card application"]', role='assistant', function_call=None, tool_calls=None))], created=1715262695, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["virtual card registration", "sign up for virtual card", "virtual card application"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get a copy of the card by email?"

Keyphrases:
946it [24:29,  1.93s/it]
ChatCompletion(id='chatcmpl-9MyTJ0QrikQe90ICLG3smKIka6xO0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["email card copy", "digital card copy", "send card via email"]', role='assistant', function_call=None, tool_calls=None))], created=1715262697, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["email card copy", "digital card copy", "send card via email"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I find the virtual card?"

Keyphrases:
947it [24:31,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyTLVbOXSUaU3feilQ3CalpoVvbJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card location", "access virtual card", "find virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262699, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["virtual card location", "access virtual card", "find virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "why do i not have a virtual card"

Keyphrases:
948it [24:33,  1.93s/it]
ChatCompletion(id='chatcmpl-9MyTNKEPiVyhWiNYjR2PNkxsYceKs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issue", "missing virtual card", "virtual card not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715262701, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["virtual card issue", "missing virtual card", "virtual card not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I order a virtual card?"

Keyphrases:
949it [24:34,  1.78s/it]
ChatCompletion(id='chatcmpl-9MyTPPdxfbbcFlG4hSLtLEK12r9w8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card order", "order new card", "digital card request"]', role='assistant', function_call=None, tool_calls=None))], created=1715262703, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["virtual card order", "order new card", "digital card request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I thought I was going to get a virtual card but I haven't received it yet, how can we resolve this?"

Keyphrases:
950it [24:36,  1.80s/it]
ChatCompletion(id='chatcmpl-9MyTQFni1CwxoSpBG316WQq3zpzO0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issue", "card not received", "resolve card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262704, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=242, total_tokens=257))
["virtual card issue", "card not received", "resolve card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please help me get a virtual card."

Keyphrases:
951it [24:37,  1.63s/it]
ChatCompletion(id='chatcmpl-9MyTSUGgiF8V036fLmzrbiVoCYk2n', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card request", "issue virtual card", "online card services"]', role='assistant', function_call=None, tool_calls=None))], created=1715262706, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["virtual card request", "issue virtual card", "online card services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I order a virtual card?"

Keyphrases:
952it [24:39,  1.64s/it]
ChatCompletion(id='chatcmpl-9MyTTdHSMCznGGBxhFDSDQMbmurS8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "order virtual card", "digital card request"]', role='assistant', function_call=None, tool_calls=None))], created=1715262707, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["virtual card", "order virtual card", "digital card request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I go to get a virtual card?"

Keyphrases:
953it [24:40,  1.52s/it]
ChatCompletion(id='chatcmpl-9MyTVzo6fD0h0r6KVuzOWQCZGJUes', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "apply for virtual card", "virtual card services"]', role='assistant', function_call=None, tool_calls=None))], created=1715262709, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["virtual card", "apply for virtual card", "virtual card services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where are the virtual cards located?"

Keyphrases:
954it [24:42,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyTWrPwjUdrSMZcrbp0oMRFx8Xol', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card access", "locate virtual card", "virtual card services"]', role='assistant', function_call=None, tool_calls=None))], created=1715262710, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["virtual card access", "locate virtual card", "virtual card services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like a virtual card- where can I purchase one?"

Keyphrases:
955it [24:44,  1.86s/it]
ChatCompletion(id='chatcmpl-9MyTYAHMwWcTklq0X2oDNaEUdJhaP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card purchase", "buy virtual card", "digital card acquisition"]', role='assistant', function_call=None, tool_calls=None))], created=1715262712, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["virtual card purchase", "buy virtual card", "digital card acquisition"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When should I receive my virtual card?"

Keyphrases:
956it [24:46,  1.78s/it]
ChatCompletion(id='chatcmpl-9MyTaMi8DM5jwpnIw4Vv7LVnAsA8f', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card delivery", "expected delivery time", "virtual card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262714, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["virtual card delivery", "expected delivery time", "virtual card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to reorder my virtual card!"

Keyphrases:
957it [24:48,  1.88s/it]
ChatCompletion(id='chatcmpl-9MyTcKub2pDf7cAYBCyN0Lb1UDp8o', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reorder virtual card", "issue new virtual card", "virtual card replacement"]', role='assistant', function_call=None, tool_calls=None))], created=1715262716, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["reorder virtual card", "issue new virtual card", "virtual card replacement"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I get a virtual card?"

Keyphrases:
958it [24:50,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyTe4tV6NDN0jH6q7o8b3HSnHRLy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "obtain virtual card", "virtual card application"]', role='assistant', function_call=None, tool_calls=None))], created=1715262718, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["virtual card", "obtain virtual card", "virtual card application"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a way to obtain a virtual card?"

Keyphrases:
959it [24:51,  1.72s/it]
ChatCompletion(id='chatcmpl-9MyTgT6z5BEXQCwEvf5Y0Rbcd1fCG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "obtain virtual card", "digital card options"]', role='assistant', function_call=None, tool_calls=None))], created=1715262720, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["virtual card", "obtain virtual card", "digital card options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I have one of the virtual cards?"

Keyphrases:
960it [24:53,  1.88s/it]
ChatCompletion(id='chatcmpl-9MyThFXHntWQGHNmfSuReA1LGW0KO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card request", "obtain virtual card", "virtual card availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715262721, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["virtual card request", "obtain virtual card", "virtual card availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will my card be accepted all over the world?"

Keyphrases:
961it [24:55,  1.74s/it]
ChatCompletion(id='chatcmpl-9MyTkurr1H2dhhikRQnGyMgoAbVHv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "global usage", "worldwide acceptance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262724, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["card acceptance", "global usage", "worldwide acceptance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Who accepts this card?"

Keyphrases:
962it [24:57,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyTlTmS1ToAphV6AJA4LBcsztbsc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "merchant acceptance", "accepted locations"]', role='assistant', function_call=None, tool_calls=None))], created=1715262725, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["card acceptance", "merchant acceptance", "accepted locations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use my card for payment all over the world?"

Keyphrases:
963it [24:59,  1.86s/it]
ChatCompletion(id='chatcmpl-9MyTn1bvz7kykeZVG0BicS4UulfGK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["global card usage", "international payment acceptance", "worldwide card use"]', role='assistant', function_call=None, tool_calls=None))], created=1715262727, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["global card usage", "international payment acceptance", "worldwide card use"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It will be fine to use at any establishment that accepts Mastercard."

Keyphrases:
964it [25:00,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyTpnAn3RoeBZvSLM1O2eVAi6BKa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Mastercard acceptance", "card usage", "using card anywhere"]', role='assistant', function_call=None, tool_calls=None))], created=1715262729, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["Mastercard acceptance", "card usage", "using card anywhere"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can the card be used?"

Keyphrases:
965it [25:01,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyTq2WupNrfevLU2Kn9oDWRMz5ST', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card usage", "card acceptance locations", "where to use card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262730, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["card usage", "card acceptance locations", "where to use card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can my card be used everywhere?"

Keyphrases:
966it [25:03,  1.63s/it]
ChatCompletion(id='chatcmpl-9MyTsKnNc5NOrZqFG7nkySHTUVEsY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card usage", "universal acceptance", "card acceptance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262732, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["card usage", "universal acceptance", "card acceptance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there any limits on where I can use my card?"

Keyphrases:
967it [25:06,  1.88s/it]
ChatCompletion(id='chatcmpl-9MyTuy4i7sssAewWVXhxw8w3lgn4F', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card usage limits", "geographical restrictions", "card acceptance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262734, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["card usage limits", "geographical restrictions", "card acceptance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What stores can I sue my card?"

Keyphrases:
968it [25:08,  1.99s/it]
ChatCompletion(id='chatcmpl-9MyTwv4BBnUTNdbVlFiPDKPJL5kWt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card usage", "accepted stores", "where to use card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262736, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["card usage", "accepted stores", "where to use card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use my card anywhere I want?"

Keyphrases:
969it [25:10,  1.93s/it]
ChatCompletion(id='chatcmpl-9MyTyRQmC0BkylvZq5wtvtPAhTiUT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card usability", "global acceptance", "using card internationally"]', role='assistant', function_call=None, tool_calls=None))], created=1715262738, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["card usability", "global acceptance", "using card internationally"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there anywhere my card will not be accepted?"

Keyphrases:
970it [25:11,  1.83s/it]
ChatCompletion(id='chatcmpl-9MyU0cogZbNXutoaVMFdgqZVBLgn3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "merchant restrictions", "card usage limitations"]', role='assistant', function_call=None, tool_calls=None))], created=1715262740, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["card acceptance", "merchant restrictions", "card usage limitations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the rules to where I can use my card?"

Keyphrases:
971it [25:13,  1.83s/it]
ChatCompletion(id='chatcmpl-9MyU1WL6imvf1L9ziVVDqLf9LWcHR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card usage rules", "card acceptance locations", "card restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715262741, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["card usage rules", "card acceptance locations", "card restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you know where my card will be accepted?"

Keyphrases:
972it [25:15,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyU3XwXH9LTtUSg8recRhODvDIlL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "accepted locations", "where to use card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262743, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["card acceptance", "accepted locations", "where to use card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What places can I use my card?"

Keyphrases:
973it [25:16,  1.77s/it]
ChatCompletion(id='chatcmpl-9MyU5njxqpK8d88bsfCV4NU0BnmMD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance locations", "card usability", "where to use card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262745, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["card acceptance locations", "card usability", "where to use card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is my card accepted everywhere?"

Keyphrases:
974it [25:18,  1.64s/it]
ChatCompletion(id='chatcmpl-9MyU7u8dxeW7VBNF5ocxPBsh2uFFe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "global usage", "accepted locations"]', role='assistant', function_call=None, tool_calls=None))], created=1715262747, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["card acceptance", "global usage", "accepted locations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What places will accept my card for payment?"

Keyphrases:
975it [25:22,  2.49s/it]
ChatCompletion(id='chatcmpl-9MyU8CeaTOcHMNVdSVWMHLjGhifci', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "payment locations", "where to use card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262748, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["card acceptance", "payment locations", "where to use card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Does this card work everywhere?"

Keyphrases:
976it [25:23,  2.09s/it]
ChatCompletion(id='chatcmpl-9MyUC3jqlpvPV12F9HmslVWvIo7wT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "card usability", "global usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715262752, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["card acceptance", "card usability", "global usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "

What businesses accept this card?"

Keyphrases:
977it [25:25,  2.03s/it]
ChatCompletion(id='chatcmpl-9MyUEbRMlQHcCj7Fu7Dk0NEOE5FpG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "merchant acceptance", "where can I use my card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262754, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=224, total_tokens=240))
["card acceptance", "merchant acceptance", "where can I use my card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I use my card?"

Keyphrases:
978it [25:27,  1.87s/it]
ChatCompletion(id='chatcmpl-9MyUGUHsHh0ABfxcThsw0ibcAiOmj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance locations", "card usage", "where to use card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262756, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["card acceptance locations", "card usage", "where to use card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Which outlets accept my card?"

Keyphrases:
979it [25:28,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyUHu4sJcSAXnhrNea0A8EJb8ymt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "outlets accepting card", "merchant compatibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715262757, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["card acceptance", "outlets accepting card", "merchant compatibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am traveling to Germany, Will I be able to use my card there?"

Keyphrases:
980it [25:30,  1.72s/it]
ChatCompletion(id='chatcmpl-9MyUJGJoFvMyzRyTieBCIVTXTa5lX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international card usage", "using card abroad", "card availability overseas"]', role='assistant', function_call=None, tool_calls=None))], created=1715262759, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["international card usage", "using card abroad", "card availability overseas"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What stores will take my credit card as payment?"

Keyphrases:
981it [25:32,  1.94s/it]
ChatCompletion(id='chatcmpl-9MyUKPwMvcNGPc3cLA7fkpzPDf4yq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card acceptance", "stores accepting credit card", "payment methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715262760, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["credit card acceptance", "stores accepting credit card", "payment methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there any place I cannot use my card?"

Keyphrases:
982it [25:34,  1.84s/it]
ChatCompletion(id='chatcmpl-9MyUNGMy7m8sabzeUSaXWdRR0v8G9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card restrictions", "card usage limitations", "prohibited card usage areas"]', role='assistant', function_call=None, tool_calls=None))], created=1715262763, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["card restrictions", "card usage limitations", "prohibited card usage areas"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will I be able to use my card anywhere?"

Keyphrases:
983it [25:35,  1.64s/it]
ChatCompletion(id='chatcmpl-9MyUOuy8oIS7nFDbkoGZX9GiEUC4O', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "global usage", "use card internationally"]', role='assistant', function_call=None, tool_calls=None))], created=1715262764, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["card acceptance", "global usage", "use card internationally"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is my card usable anywhere?"

Keyphrases:
984it [25:36,  1.54s/it]
ChatCompletion(id='chatcmpl-9MyUPaDylvSnjI5ahlgYKHsCQIIBC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "global usage", "card usability"]', role='assistant', function_call=None, tool_calls=None))], created=1715262765, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["card acceptance", "global usage", "card usability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it acceptable to use my card anywhere?"

Keyphrases:
985it [25:39,  1.87s/it]
ChatCompletion(id='chatcmpl-9MyURhm9X4nThX97gyAg8Ix2fdChJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "global usage", "using card internationally"]', role='assistant', function_call=None, tool_calls=None))], created=1715262767, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["card acceptance", "global usage", "using card internationally"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use my card everywhere?"

Keyphrases:
986it [25:41,  1.89s/it]
ChatCompletion(id='chatcmpl-9MyUTXrY72HIZJo41UaENUaK6Kwen', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "global usage", "use card internationally"]', role='assistant', function_call=None, tool_calls=None))], created=1715262769, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["card acceptance", "global usage", "use card internationally"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is my card accepted?"

Keyphrases:
987it [25:42,  1.77s/it]
ChatCompletion(id='chatcmpl-9MyUV7AeK3icUYDJpOWM7v1l7Ev9l', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "accepted locations", "usage areas"]', role='assistant', function_call=None, tool_calls=None))], created=1715262771, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["card acceptance", "accepted locations", "usage areas"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I pay with my debit or credit card?"

Keyphrases:
988it [25:44,  1.68s/it]
ChatCompletion(id='chatcmpl-9MyUXOKMdNYPVJZyQLXXhUno4WGaX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment locations", "card acceptance", "places accepting card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262773, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["payment locations", "card acceptance", "places accepting card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where should my card work?"

Keyphrases:
989it [25:46,  1.89s/it]
ChatCompletion(id='chatcmpl-9MyUYtxOiIiysgJ6N39IFnJaEXo3o', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "card usability", "card usage locations"]', role='assistant', function_call=None, tool_calls=None))], created=1715262774, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["card acceptance", "card usability", "card usage locations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "areas card is accpeted"

Keyphrases:
990it [25:48,  1.82s/it]
ChatCompletion(id='chatcmpl-9MyUbpyAS9JFGiHc6pugOkGeJdm9X', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "accepted locations", "usage areas"]', role='assistant', function_call=None, tool_calls=None))], created=1715262777, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["card acceptance", "accepted locations", "usage areas"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "places i can use the card"

Keyphrases:
991it [25:49,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyUc8BJkSAGQRDKwaIdlUv8KWn1p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance locations", "card usage", "where to use card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262778, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["card acceptance locations", "card usage", "where to use card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I make online purchases with my card?"

Keyphrases:
992it [25:51,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyUeOAe8wGJaebBwseYW8v0f10td', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["online purchases", "card usage", "e-commerce eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715262780, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["online purchases", "card usage", "e-commerce eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Does every place of business accept this card?"

Keyphrases:
993it [25:53,  1.94s/it]
ChatCompletion(id='chatcmpl-9MyUff7cMBhhSWxGtxnjL8YtDGayB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "merchant compatibility", "accepted locations"]', role='assistant', function_call=None, tool_calls=None))], created=1715262781, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["card acceptance", "merchant compatibility", "accepted locations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What places will accept my card?"

Keyphrases:
994it [25:56,  2.05s/it]
ChatCompletion(id='chatcmpl-9MyUicWPasElb8Cyi0EeN673Q1gpO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "merchant compatibility", "where to use card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262784, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["card acceptance", "merchant compatibility", "where to use card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use my card anywere?"

Keyphrases:
995it [25:57,  1.82s/it]
ChatCompletion(id='chatcmpl-9MyUkAwAQNar55X9mNFKiVRUKTExC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "global card usage", "international spending"]', role='assistant', function_call=None, tool_calls=None))], created=1715262786, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card acceptance", "global card usage", "international spending"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will any business take this card?"

Keyphrases:
996it [25:58,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyUlfa1Ygyj5knZZpgBweNfzpRpv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "merchant compatibility", "business card use"]', role='assistant', function_call=None, tool_calls=None))], created=1715262787, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["card acceptance", "merchant compatibility", "business card use"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will filling stations accept my card?"

Keyphrases:
997it [26:00,  1.65s/it]
ChatCompletion(id='chatcmpl-9MyUnixFw1F6ie32CuHdzirONWN4Y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "use card at filling stations", "merchant acceptance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262789, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["card acceptance", "use card at filling stations", "merchant acceptance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where am I able to use the card?"

Keyphrases:
998it [26:03,  2.14s/it]
ChatCompletion(id='chatcmpl-9MyUom0mhgjYowPDks28zZqtNcYNl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "card usage locations", "where to use card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262790, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["card acceptance", "card usage locations", "where to use card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What can I use my card to pay for?"

Keyphrases:
999it [26:05,  1.95s/it]
ChatCompletion(id='chatcmpl-9MyUr20dAjR9mx7rrAXTIufFHpVqK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card usage", "payment options", "where to use card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262793, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["card usage", "payment options", "where to use card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Who accepts my card?"

Keyphrases:
1000it [26:07,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyUtunSnCZVbJmvHUFrxa86IW88X', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "merchant acceptance", "where can I use my card"]', role='assistant', function_call=None, tool_calls=None))], created=1715262795, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=223, total_tokens=239))
["card acceptance", "merchant acceptance", "where can I use my card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top-up was cancelled; will I receive a refund?"

Keyphrases:
1001it [26:08,  1.87s/it]
ChatCompletion(id='chatcmpl-9MyUvPQcPdQFzi15vzuBg6DEIJGax', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up refund", "cancelled top-up", "refund status"]', role='assistant', function_call=None, tool_calls=None))], created=1715262797, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["top-up refund", "cancelled top-up", "refund status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I fix a reverted top up?"

Keyphrases:
1002it [26:11,  2.05s/it]
ChatCompletion(id='chatcmpl-9MyUxAzGefeRw9SguWSlexxtejTIQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "reverted top up", "fix top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262799, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["top up issue", "reverted top up", "fix top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to tell if my top up has reverted?"

Keyphrases:
1003it [26:13,  2.20s/it]
ChatCompletion(id='chatcmpl-9MyV0Ykhyk8oRfjPLko8ICVr5FYxF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up status", "reverted transaction", "transaction status"]', role='assistant', function_call=None, tool_calls=None))], created=1715262802, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["top up status", "reverted transaction", "transaction status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top-up showed as complete, but it's no longer there! What's going on here?"

Keyphrases:
1004it [26:17,  2.49s/it]
ChatCompletion(id='chatcmpl-9MyV2mSGJj7RE9qmXv6pPmWfpbRSL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "missing top-up", "completed top-up not showing"]', role='assistant', function_call=None, tool_calls=None))], created=1715262804, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=238, total_tokens=255))
["top-up issue", "missing top-up", "completed top-up not showing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hi, i don't know what's going on i've just paid for my top up twice by accident can you help me get a refund please."

Keyphrases:
1005it [26:21,  3.20s/it]
ChatCompletion(id='chatcmpl-9MyV5JMrYFlBqcpXuNtc9OK7l6bWq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double payment", "refund request", "accidental payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715262807, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=248, total_tokens=261))
["double payment", "refund request", "accidental payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It seems my top up is reverted?"

Keyphrases:
1006it [26:23,  2.81s/it]
ChatCompletion(id='chatcmpl-9MyVAkXsKmYJb1vyXDDNFI1GGvvP4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "reverted transaction", "failed top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262812, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["top up issue", "reverted transaction", "failed top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app wouldn't accept my top up."

Keyphrases:
1007it [26:25,  2.41s/it]
ChatCompletion(id='chatcmpl-9MyVCj0h2ycvUYET0U3dhMTQeYJCU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "payment failure", "app transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715262814, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["top up issue", "payment failure", "app transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I topped up my account and even though it was confirmed at first, the money isn't there anymore! why did this happen, and where did my money go?"

Keyphrases:
1008it [26:26,  2.15s/it]
ChatCompletion(id='chatcmpl-9MyVDYD6H7Cvp1puhp8Q0GS3mCUDc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing funds", "transaction reversal", "top-up issues", "account discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715262815, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=251, total_tokens=268))
["missing funds", "transaction reversal", "top-up issues", "account discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I believe my money did not go through with my top up, was there a problem on your end?"

Keyphrases:
1009it [26:28,  1.94s/it]
ChatCompletion(id='chatcmpl-9MyVFiXqE2e6VTKmzsji4KCSfrHvP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "failed transaction", "payment not processed"]', role='assistant', function_call=None, tool_calls=None))], created=1715262817, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=239, total_tokens=253))
["top up issue", "failed transaction", "payment not processed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top-up was reverted, why did this happen?"

Keyphrases:
1010it [26:31,  2.47s/it]
ChatCompletion(id='chatcmpl-9MyVGO8fVK5QQu5FN1pNdZRn8bY6J', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up reversal", "reverted payment", "failed top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262818, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["top-up reversal", "reverted payment", "failed top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I put money into my account for the minimum balance but the application didn't accept."

Keyphrases:
1011it [26:33,  2.11s/it]
ChatCompletion(id='chatcmpl-9MyVKmnzVajAG5AmrJOStPp6HavH1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["minimum balance", "deposit not recognized", "account funding issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262822, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["minimum balance", "deposit not recognized", "account funding issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me if my top-up has been cancelled?"

Keyphrases:
1012it [26:34,  1.89s/it]
ChatCompletion(id='chatcmpl-9MyVLnSYwMwYTVFj2lZm7e5IczgXb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "cancelled top-up", "transaction status"]', role='assistant', function_call=None, tool_calls=None))], created=1715262823, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["top-up status", "cancelled top-up", "transaction status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got topped up but the application reverted it."

Keyphrases:
1013it [26:36,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyVMXoO5dpeK6vMjbiEr5CI01t0B', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up reversal", "transaction reversal", "failed top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262824, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top-up reversal", "transaction reversal", "failed top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why would my top up be cancelled?"

Keyphrases:
1014it [26:37,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyVOBomSejNfnbqL8Ahhv0LTxIpO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up cancellation", "failed payment", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262826, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["top up cancellation", "failed payment", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There appears to have been a reversion in my top up"

Keyphrases:
1015it [26:39,  1.74s/it]
ChatCompletion(id='chatcmpl-9MyVQ4iLBYNQUfNUIY5zKrcrWvkuR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up reversal", "reversed transaction", "failed top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262828, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["top up reversal", "reversed transaction", "failed top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The application reverted my top-up."

Keyphrases:
1016it [26:42,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyVR087rL7oeKuC6RPsFqYxLU72q', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up reversal", "failed top-up", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262829, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["top-up reversal", "failed top-up", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think my top-up was cancelled."

Keyphrases:
1017it [26:43,  1.86s/it]
ChatCompletion(id='chatcmpl-9MyVUiKLnTwzEpS3PziBsjMlUhz58', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "cancelled top-up", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262832, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["top-up status", "cancelled top-up", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I believed crypto top up with something you offered. This does not seem to be working. The money has been removed from my account though so what's going on?"

Keyphrases:
1018it [26:57,  5.49s/it]
ChatCompletion(id='chatcmpl-9MyVV0jFdodZBkfxhnvKLYytV8kEs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["crypto top up issue", "funds debited no service", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715262833, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=251, total_tokens=269))
["crypto top up issue", "funds debited no service", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I topped up but the app reverted it"

Keyphrases:
1019it [26:59,  4.32s/it]
ChatCompletion(id='chatcmpl-9MyVj9gmT5mgQAqEFTeXcMW8F0hg5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "failed transaction", "reverted payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715262847, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["top-up issue", "failed transaction", "reverted payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I went to top up and it is no longer there.  Was it sent back?"

Keyphrases:
1020it [27:00,  3.51s/it]
ChatCompletion(id='chatcmpl-9MyVlqzLDRKCkwTIwy6fmZEEP0goA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "failed top up", "reversed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262849, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["top up issue", "failed top up", "reversed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What happened to my top-up?"

Keyphrases:
1021it [27:02,  2.90s/it]
ChatCompletion(id='chatcmpl-9MyVnCGEKz0mgLdiOk5X7GIfo8aOq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "top-up issue", "failed top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715262851, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["top-up status", "top-up issue", "failed top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me why my top up was reverted?"

Keyphrases:
1022it [27:03,  2.52s/it]
ChatCompletion(id='chatcmpl-9MyVodJUU0Uw1RF86dkkvu19vA0Wn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up reversal", "reverted transaction", "payment reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262852, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["top up reversal", "reverted transaction", "payment reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "For what reason would a top up be reverted and returned to my account?"

Keyphrases:
1023it [27:06,  2.65s/it]
ChatCompletion(id='chatcmpl-9MyVqVe0INjTn8xznq5FqE682IZnT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up reversal", "reverted transaction", "funds return"]', role='assistant', function_call=None, tool_calls=None))], created=1715262854, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["top up reversal", "reverted transaction", "funds return"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When I topped up, the app reverted my funds."

Keyphrases:
1024it [27:09,  2.62s/it]
ChatCompletion(id='chatcmpl-9MyVtDbYtBR2dLSkOVT6zPQUwYNfC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["funds reverting", "top-up issue", "transaction reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262857, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["funds reverting", "top-up issue", "transaction reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What happened to where my top-up was canceled?"

Keyphrases:
1025it [27:11,  2.46s/it]
ChatCompletion(id='chatcmpl-9MyVvlfBnEWbsnVPVQz9vXv8M6GdS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "canceled top-up", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262859, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["top-up status", "canceled top-up", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tryed to make a top-up with cryptocurrency but the payment was referted."

Keyphrases:
1026it [27:13,  2.41s/it]
ChatCompletion(id='chatcmpl-9MyVylfRnwZOZoGr0XOmdvHKkYNzk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cryptocurrency top-up", "payment reverted", "issue with crypto payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715262862, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=236, total_tokens=252))
["cryptocurrency top-up", "payment reverted", "issue with crypto payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app reverted my top off."

Keyphrases:
1027it [27:15,  2.11s/it]
ChatCompletion(id='chatcmpl-9MyW0fNoXWM57qmGWILmTbat5Rt7F', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up reversal", "app transaction issue", "reverted payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715262864, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["top up reversal", "app transaction issue", "reverted payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app reverted my action when I topped up."

Keyphrases:
1028it [27:16,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyW11J4ZuyeuM1ky5T5HBXyIKETN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "app error", "reverted transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262865, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top-up issue", "app error", "reverted transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Was my top up reversed?"

Keyphrases:
1029it [27:20,  2.37s/it]
ChatCompletion(id='chatcmpl-9MyW2wNrOuyh5FTpQ6kx6QUqf8iEo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up status", "reversal confirmation", "transaction reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262866, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["top up status", "reversal confirmation", "transaction reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I see my top-up was canceled, but why?"

Keyphrases:
1030it [27:21,  2.14s/it]
ChatCompletion(id='chatcmpl-9MyW6gNwJXPbUWypCGawaAICoGpnm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "canceled top-up", "reason for cancellation"]', role='assistant', function_call=None, tool_calls=None))], created=1715262870, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["top-up status", "canceled top-up", "reason for cancellation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you know if my top-up has been cancelled?"

Keyphrases:
1031it [27:23,  1.98s/it]
ChatCompletion(id='chatcmpl-9MyW8tvvY0KCSCij0h2J8eKbDUWJh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "cancelled top-up", "top-up confirmation"]', role='assistant', function_call=None, tool_calls=None))], created=1715262872, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["top-up status", "cancelled top-up", "top-up confirmation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "has my top-up has been cancelled"

Keyphrases:
1032it [27:25,  2.06s/it]
ChatCompletion(id='chatcmpl-9MyW9ck4GRDMFIAhUR9L0uH9Qsxv8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "cancellation status", "payment reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262873, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["top-up status", "cancellation status", "payment reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top-up was revoked."

Keyphrases:
1033it [27:27,  2.05s/it]
ChatCompletion(id='chatcmpl-9MyWBbfRD7b8juCEGAHCe8IWksy0W', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "revoked top-up", "payment reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262875, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["top-up issue", "revoked top-up", "payment reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Causes of top-up cancellation"

Keyphrases:
1034it [27:28,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyWDBmcdoRBmefIxnbRaH7KsxKwX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up cancellation", "payment failure", "transaction issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715262877, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["top-up cancellation", "payment failure", "transaction issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app reverted what I topped up."

Keyphrases:
1035it [27:30,  1.65s/it]
ChatCompletion(id='chatcmpl-9MyWFkqg9slVC7syt3KssqFCkret0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up reversal", "funds not credited", "transaction reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262879, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["top-up reversal", "funds not credited", "transaction reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Has my top up been reverted?"

Keyphrases:
1036it [27:31,  1.55s/it]
ChatCompletion(id='chatcmpl-9MyWGYQGH9DwAZVfTABVtMjt9FoMc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up status", "reverted transaction", "top up reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715262880, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["top up status", "reverted transaction", "top up reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Im very upset as my top-up was canceled and I have no idea why."

Keyphrases:
1037it [27:32,  1.55s/it]
ChatCompletion(id='chatcmpl-9MyWHJVe1i0TpiVi6yrNSQVKe5Wqf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "canceled top-up", "top-up failure explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715262881, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=234, total_tokens=251))
["top-up issue", "canceled top-up", "top-up failure explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top-up has been cancelled."

Keyphrases:
1038it [27:34,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyWJ93swwmMRGrFscTxMWflu0Ct5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "cancelled top-up", "transaction status"]', role='assistant', function_call=None, tool_calls=None))], created=1715262883, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["top-up status", "cancelled top-up", "transaction status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "On my last transaction it seem that my top-up was not successful."

Keyphrases:
1039it [27:36,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyWLYYHvC3XcTAfTStGuAsbnrD6M', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction issue", "top-up failure", "failed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262885, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["transaction issue", "top-up failure", "failed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'd like to know why my top-up was canceled please."

Keyphrases:
1040it [27:39,  2.15s/it]
ChatCompletion(id='chatcmpl-9MyWMo4MYKHUD2H2pNUn0Pea7HSb7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up cancellation", "canceled top-up reason", "funding issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715262886, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["top-up cancellation", "canceled top-up reason", "funding issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried making an update to my balance using cheque just yesterday but it doesn't appear to have worked. Should this not be a faster process? I need you to please check over my account because something has went wrong."

Keyphrases:
1041it [27:41,  2.03s/it]
ChatCompletion(id='chatcmpl-9MyWQl1ocgz6rW07MFRURPpo0j2be', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit issue", "balance update failure", "account review request"]', role='assistant', function_call=None, tool_calls=None))], created=1715262890, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=262, total_tokens=278))
["cheque deposit issue", "balance update failure", "account review request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How come I don't see my deposit in my account yet?"

Keyphrases:
1042it [27:44,  2.38s/it]
ChatCompletion(id='chatcmpl-9MyWRydXv0aYUQZWlVMR3RRgfCVHX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit status", "missing deposit", "deposit not showing"]', role='assistant', function_call=None, tool_calls=None))], created=1715262891, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["deposit status", "missing deposit", "deposit not showing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a reason why my account isn't updating because I used a check to  balance my account?"

Keyphrases:
1043it [27:49,  2.96s/it]
ChatCompletion(id='chatcmpl-9MyWVcBcLObsgXXeMrtLQziTV4HOd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account update", "check deposit", "balance inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715262895, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=239, total_tokens=251))
["account update", "check deposit", "balance inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't know why the deposit I made a week ago still hasn't showed up, I really need the money now."

Keyphrases:
1044it [27:52,  3.11s/it]
ChatCompletion(id='chatcmpl-9MyWZ5AmWQITfTqSqWircAaT0mrxE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing deposit", "deposit delay", "urgent deposit issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262899, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=243, total_tokens=256))
["missing deposit", "deposit delay", "urgent deposit issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a cash deposit almost a week ago but it's still not there!! please sort this out asap I need the money"

Keyphrases:
1045it [27:54,  2.75s/it]
ChatCompletion(id='chatcmpl-9MyWcoXQHiFpFYv7fnFb1RovE3iya', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit issue", "delayed deposit", "deposit not credited"]', role='assistant', function_call=None, tool_calls=None))], created=1715262902, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=245, total_tokens=260))
["cash deposit issue", "delayed deposit", "deposit not credited"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is my cash deposit?"

Keyphrases:
1046it [27:58,  3.19s/it]
ChatCompletion(id='chatcmpl-9MyWeft0pmX8XcOCic3omKSPjdprP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit location", "deposit status", "missing deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262904, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["cash deposit location", "deposit status", "missing deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I get the cash deposit to show up on my account?"

Keyphrases:
1047it [28:00,  2.84s/it]
ChatCompletion(id='chatcmpl-9MyWjLLj7fwycAb9aDRfbdJca4KHH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit", "deposit not showing", "update account balance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262909, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["cash deposit", "deposit not showing", "update account balance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will I see the cash I deposited this morning as available?"

Keyphrases:
1048it [28:02,  2.37s/it]
ChatCompletion(id='chatcmpl-9MyWlYS8h0pJZiWbXOziRWwTP24UN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit availability", "cash deposit processing time", "funds clearance time"]', role='assistant', function_call=None, tool_calls=None))], created=1715262911, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["deposit availability", "cash deposit processing time", "funds clearance time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "cash from this morning has not deposited"

Keyphrases:
1049it [28:03,  2.05s/it]
ChatCompletion(id='chatcmpl-9MyWmwglQK5xBaxxguELWK6wj8e4I', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit status", "cash deposit issue", "failed deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262912, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["deposit status", "cash deposit issue", "failed deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is the cash from my cheque I recently deposited?"

Keyphrases:
1050it [28:05,  2.18s/it]
ChatCompletion(id='chatcmpl-9MyWoKsxmnVZCMt1FRvRzi6sL5VpV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit", "cheque clearance status", "deposited funds availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715262914, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=229, total_tokens=247))
["cheque deposit", "cheque clearance status", "deposited funds availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Cash deposit to my account but it has not appeared."

Keyphrases:
1051it [28:07,  1.97s/it]
ChatCompletion(id='chatcmpl-9MyWqM2IyI4Y53IFrMqVOO7oMdHG3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit", "deposit not credited", "missing deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262916, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["cash deposit", "deposit not credited", "missing deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When I deposit cheques and cash, my balance does not update."

Keyphrases:
1052it [28:10,  2.22s/it]
ChatCompletion(id='chatcmpl-9MyWrGyEnqlzYWMKovOe9wzRYwZfv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit update", "balance not updating", "cheque deposit issue", "cash deposit issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262917, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=20, prompt_tokens=232, total_tokens=252))
["deposit update", "balance not updating", "cheque deposit issue", "cash deposit issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a deposit this morning but it is still pending?"

Keyphrases:
1053it [28:13,  2.53s/it]
ChatCompletion(id='chatcmpl-9MyWuUdET2syJHvNGUogjQfzGLe1N', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit status", "pending deposit", "transaction delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715262920, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["deposit status", "pending deposit", "transaction delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "cash deposit to my account has shown a red flag."

Keyphrases:
1054it [28:15,  2.30s/it]
ChatCompletion(id='chatcmpl-9MyWx0N3jJYHwN28u0jPZZCbxOKtw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit issue", "cash deposit red flag", "transaction alert"]', role='assistant', function_call=None, tool_calls=None))], created=1715262923, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["deposit issue", "cash deposit red flag", "transaction alert"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have paid money into my account but it doesn't show."

Keyphrases:
1055it [28:16,  2.11s/it]
ChatCompletion(id='chatcmpl-9MyWziFEDeFWUEwzOgb5CqUXfBQWQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit not showing", "missing deposit", "account update delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715262925, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["deposit not showing", "missing deposit", "account update delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The balance on my account wasn't updated after I made a depost."

Keyphrases:
1056it [28:18,  1.89s/it]
ChatCompletion(id='chatcmpl-9MyX169FaJ5RoZTdyxgqtoS5yc9jZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit update", "account balance", "balance not updated"]', role='assistant', function_call=None, tool_calls=None))], created=1715262927, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["deposit update", "account balance", "balance not updated"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are cheques accepted to my account? Mine didn't seem to work."

Keyphrases:
1057it [28:20,  1.89s/it]
ChatCompletion(id='chatcmpl-9MyX2kWZVcb3Pjj3nGbwt4MilcR5i', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque acceptance", "cheque deposit issue", "account deposit eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715262928, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["cheque acceptance", "cheque deposit issue", "account deposit eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I deposited a check but my balance is still the same."

Keyphrases:
1058it [28:21,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyX4COlhBfi4LqvIqi7Kod0HTjfH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["check deposit", "balance not updated", "pending deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262930, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["check deposit", "balance not updated", "pending deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "IM still waiting for my account to update from a cash deposit?"

Keyphrases:
1059it [28:23,  1.83s/it]
ChatCompletion(id='chatcmpl-9MyX5e9MlHp4fl8ykc3WF2ZKPU6a9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account update delay", "cash deposit processing", "deposit status"]', role='assistant', function_call=None, tool_calls=None))], created=1715262931, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["account update delay", "cash deposit processing", "deposit status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I Submitted a cheque couple days ago, nothing happened to my account yet.Would you please check What could be the possible issue?"

Keyphrases:
1060it [28:26,  2.12s/it]
ChatCompletion(id='chatcmpl-9MyX7hFQv6pNt1iufJn7TA5UAUaxJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque processing", "cheque issue", "account update delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715262933, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=244, total_tokens=259))
["cheque processing", "cheque issue", "account update delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is my deposit?"

Keyphrases:
1061it [28:27,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyXAfUbrmQR9iFM9NJxEu1NgGsib', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit status", "missing deposit", "account deposit query"]', role='assistant', function_call=None, tool_calls=None))], created=1715262936, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["deposit status", "missing deposit", "account deposit query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My bank statement doesn't show the cash deposit I made recently."

Keyphrases:
1062it [28:28,  1.72s/it]
ChatCompletion(id='chatcmpl-9MyXCFYz1H7zK2paYAjZIUQLL7P90', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing deposit", "bank statement discrepancy", "recent deposit not showing"]', role='assistant', function_call=None, tool_calls=None))], created=1715262938, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["missing deposit", "bank statement discrepancy", "recent deposit not showing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My cash deposit from a week ago hasn't shown up. I need the money - how quickly can you sort this out?"

Keyphrases:
1063it [28:32,  2.18s/it]
ChatCompletion(id='chatcmpl-9MyXDElgf0DQglLoF5Rps2ym7heIr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing deposit", "deposit issue", "urgent deposit resolution"]', role='assistant', function_call=None, tool_calls=None))], created=1715262939, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=243, total_tokens=256))
["missing deposit", "deposit issue", "urgent deposit resolution"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why didn't my balance update after my cash or checque deposit?"

Keyphrases:
1064it [28:33,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyXGZXHDc7rvxTkpFbTTnmYAmNJg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["balance update", "deposit processing", "transaction delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715262942, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=233, total_tokens=245))
["balance update", "deposit processing", "transaction delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is the cash deposit not showing up in my account?"

Keyphrases:
1065it [28:34,  1.73s/it]
ChatCompletion(id='chatcmpl-9MyXH2m8I9jNSaW74ZJX4DfTpEAWE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit issue", "deposit not credited", "missing deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262943, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["cash deposit issue", "deposit not credited", "missing deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a deposit of cash and check that has not been added to my balance."

Keyphrases:
1066it [28:37,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyXJhRARtpmyAcu9LgkOwu0FhScA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit issue", "uncredited deposit", "balance update"]', role='assistant', function_call=None, tool_calls=None))], created=1715262945, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=235, total_tokens=248))
["deposit issue", "uncredited deposit", "balance update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why hasn't my balance increased after depositing a check?"

Keyphrases:
1067it [28:38,  1.74s/it]
ChatCompletion(id='chatcmpl-9MyXLRMYqAOA4IhX7DmZQCmu0nRgp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["check deposit", "balance update", "delayed deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715262947, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["check deposit", "balance update", "delayed deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why does my account not accept cash deposits?"

Keyphrases:
1068it [28:39,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyXM8vmzkkU1W5Mz5wsAhAMQ5B05', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit issue", "account restriction", "deposit acceptance"]', role='assistant', function_call=None, tool_calls=None))], created=1715262948, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["cash deposit issue", "account restriction", "deposit acceptance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What happened to the cash that I tried to deposit into my account? It's gone!"

Keyphrases:
1069it [28:41,  1.51s/it]
ChatCompletion(id='chatcmpl-9MyXOXswrcVo642c14cgruzbTKm3e', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit issue", "missing deposit", "deposit not showing"]', role='assistant', function_call=None, tool_calls=None))], created=1715262950, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=236, total_tokens=250))
["cash deposit issue", "missing deposit", "deposit not showing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I had a cheque deposited, but I still haven't seen the cash."

Keyphrases:
1070it [28:42,  1.49s/it]
ChatCompletion(id='chatcmpl-9MyXPGrjBLMssLhGLeIqVDbSgfrom', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit", "deposit not credited", "missing funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715262951, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["cheque deposit", "deposit not credited", "missing funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "A cheque deposit hasn't posted to my account, when will my balance update?"

Keyphrases:
1071it [28:45,  2.06s/it]
ChatCompletion(id='chatcmpl-9MyXQQvqXMcjl8ZFYULH3z8Dr6FYE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit delay", "balance update", "deposit posting time"]', role='assistant', function_call=None, tool_calls=None))], created=1715262952, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["cheque deposit delay", "balance update", "deposit posting time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I submitted a cash deposit to my account but it hasn't posted yet."

Keyphrases:
1072it [28:47,  2.03s/it]
ChatCompletion(id='chatcmpl-9MyXUufRDK1Hnl3FibOEB5sVnT5ha', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit delay", "deposit not posted", "account update delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715262956, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["cash deposit delay", "deposit not posted", "account update delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I sent a cheque  a few days ago and nothing has happened to my account yet. Can you please check on this for me?"

Keyphrases:
1073it [28:49,  1.82s/it]
ChatCompletion(id='chatcmpl-9MyXWvyqpd2saWW5mf6yH7FiF7iHX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque processing", "cheque status", "cheque not cleared"]', role='assistant', function_call=None, tool_calls=None))], created=1715262958, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=245, total_tokens=261))
["cheque processing", "cheque status", "cheque not cleared"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Has the check I deposited cleared to I can get the cash?"

Keyphrases:
1074it [28:50,  1.64s/it]
ChatCompletion(id='chatcmpl-9MyXXzdcJIqUvbAksYJWGHHj0eSza', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["check clearance", "deposit status", "funds availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715262959, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["check clearance", "deposit status", "funds availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does it take to process cheque deposits?"

Keyphrases:
1075it [28:51,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyXY6HtDrMpnHm90TjKfH6XTHNpf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit time", "deposit processing time", "cheque clearance duration"]', role='assistant', function_call=None, tool_calls=None))], created=1715262960, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["cheque deposit time", "deposit processing time", "cheque clearance duration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How come my cash deposit is not showing up. This can't be right. There must be some mistake. Where did my cash go. You better not have lost it as I need this money asap."

Keyphrases:
1076it [28:53,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyXaC5YiTlQqiabJL9lTturszwTf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit issue", "missing deposit", "deposit not showing"]', role='assistant', function_call=None, tool_calls=None))], created=1715262962, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=260, total_tokens=274))
["cash deposit issue", "missing deposit", "deposit not showing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I deposited cash this morning and I am still waiting"

Keyphrases:
1077it [28:55,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyXbR5GyOaN8zKEuZqyK5s8Xlm9F', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit status", "cash deposit delay", "deposit not reflecting"]', role='assistant', function_call=None, tool_calls=None))], created=1715262963, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["deposit status", "cash deposit delay", "deposit not reflecting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Balance hasn't been updated following a cheque or cash deposit"

Keyphrases:
1078it [28:56,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyXd6UoZqguHq3mpCKyoacgy1CoN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["balance update", "cheque deposit", "cash deposit", "deposit not reflecting"]', role='assistant', function_call=None, tool_calls=None))], created=1715262965, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=230, total_tokens=248))
["balance update", "cheque deposit", "cash deposit", "deposit not reflecting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tired to deposit some cash into my account but it's not there"

Keyphrases:
1079it [28:59,  1.88s/it]
ChatCompletion(id='chatcmpl-9MyXeZDbEnCB6ybnfdmSM6CCogeXr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit issue", "missing deposit", "cash deposit not reflecting"]', role='assistant', function_call=None, tool_calls=None))], created=1715262966, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["deposit issue", "missing deposit", "cash deposit not reflecting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I sent you a cheque couple days ago, nothing happened to my account yet! This is unacceptable, where is my money??"

Keyphrases:
1080it [29:01,  1.89s/it]
ChatCompletion(id='chatcmpl-9MyXhXhz1L2xTSK4ZJtfLAaaXwYna', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque processing", "funds not credited", "cheque deposit issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715262969, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=244, total_tokens=261))
["cheque processing", "funds not credited", "cheque deposit issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a strange payment in my statement"

Keyphrases:
1081it [29:02,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyXjUFT5eZZINA2QKqxB86DMbUt6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "fraudulent charge", "statement query"]', role='assistant', function_call=None, tool_calls=None))], created=1715262971, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["unrecognized transaction", "fraudulent charge", "statement query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a charge on my card that I did not make"

Keyphrases:
1082it [29:03,  1.65s/it]
ChatCompletion(id='chatcmpl-9MyXkw7kbQdW5Zna2GYFBSteJQ8Fx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized charge", "dispute transaction", "fraudulent charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715262972, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["unauthorized charge", "dispute transaction", "fraudulent charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I saw a payment i did not do"

Keyphrases:
1083it [29:06,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyXmi29yhzmPCHtEHZuomiPz8Il2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized payment", "fraudulent transaction", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262974, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["unauthorized payment", "fraudulent transaction", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a payment that is not mine in the app.  Please advise/"

Keyphrases:
1084it [29:08,  1.84s/it]
ChatCompletion(id='chatcmpl-9MyXoD0YA2J3UzknxjRVN00vBt3S0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraudulent charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262976, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=234, total_tokens=250))
["unauthorized transaction", "fraudulent charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "An unauthorized payment is in my app"

Keyphrases:
1085it [29:09,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyXqwpmiy5EuBYs8FmjdhauMBApE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized payment", "fraudulent transaction", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262978, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["unauthorized payment", "fraudulent transaction", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I did not make this card payment."

Keyphrases:
1086it [29:10,  1.67s/it]
ChatCompletion(id='chatcmpl-9MyXryLP7qcWB7gZfHZN3BvyemuQG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraudulent charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262979, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["unauthorized transaction", "fraudulent charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What should I do if I see a payment I didn't make?"

Keyphrases:
1087it [29:12,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyXts1NyWlKbOQPZlqWuxjX9D0ks', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized payment", "fraudulent charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262981, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["unauthorized payment", "fraudulent charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I found an unauthorized card payment"

Keyphrases:
1088it [29:14,  1.77s/it]
ChatCompletion(id='chatcmpl-9MyXutcsZnTheCBDLowEFpqfOaYlj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized payment", "fraudulent charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262982, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["unauthorized payment", "fraudulent charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "there is a transaction on my account that i didnt make"

Keyphrases:
1089it [29:16,  1.69s/it]
ChatCompletion(id='chatcmpl-9MyXwHzt9cdxmtVW2j3NnZTlov1vP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraudulent charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262984, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["unauthorized transaction", "fraudulent charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't recall making that payment?"

Keyphrases:
1090it [29:17,  1.55s/it]
ChatCompletion(id='chatcmpl-9MyXyseN9gx6xWQwFhX4H0w1UJlNn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized payment", "dispute transaction", "payment recall"]', role='assistant', function_call=None, tool_calls=None))], created=1715262986, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["unauthorized payment", "dispute transaction", "payment recall"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There are some payments with my card that I don't know where they are coming from. Just checked today and it's been since a couple days as well! What to I do? Can I revert this retrospectively? My card needs to be frozen immediately as well!"

Keyphrases:
1091it [29:19,  1.64s/it]
ChatCompletion(id='chatcmpl-9MyXz0yj3QYA8k1p9Dzfuzx0QCzYj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transactions", "fraudulent charges", "freeze card", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262987, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=20, prompt_tokens=272, total_tokens=292))
["unrecognized transactions", "fraudulent charges", "freeze card", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Has someone accessed my card there are payments I did not make that are showing up on the app."

Keyphrases:
1092it [29:20,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyY1esdZQHsWWoXm1CqhaqAH3NUa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transactions", "fraud detection", "security breach"]', role='assistant', function_call=None, tool_calls=None))], created=1715262989, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=238, total_tokens=252))
["unauthorized transactions", "fraud detection", "security breach"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There are some strange charges on my card that I didn't make from a few days ago.  Is my card stolen and if so should I cancel it?  Will I get refunded the charges?"

Keyphrases:
1093it [29:22,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyY2O1haCROSa7Y8F0DX3Ej960WH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fraudulent charges", "cancel card", "refund unauthorized transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715262990, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=258, total_tokens=273))
["fraudulent charges", "cancel card", "refund unauthorized transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why would there be a payment on my account I don't recognize?"

Keyphrases:
1094it [29:24,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyY4Pd6Vz2MwknY3HzCi5PMIUWdy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized payment", "fraudulent charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262992, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["unrecognized payment", "fraudulent charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a payment I didn't do"

Keyphrases:
1095it [29:25,  1.62s/it]
ChatCompletion(id='chatcmpl-9MyY6oXyMqh47pP37kHk6djmNOXGQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized payment", "fraudulent charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262994, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["unauthorized payment", "fraudulent charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a payment that is not mine."

Keyphrases:
1096it [29:32,  3.14s/it]
ChatCompletion(id='chatcmpl-9MyY7OqLCtDyrQI1mi5UOihFHPevZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraudulent charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715262995, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["unauthorized transaction", "fraudulent charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you freeze my account?  I just saw there are transactions on my account that I don't recognize.  How can I fix this?"

Keyphrases:
1097it [29:34,  2.87s/it]
ChatCompletion(id='chatcmpl-9MyYEqwG6DzNCABc9ELEF4N1rAQ68', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["freeze account", "unrecognized transactions", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715263002, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=247, total_tokens=260))
["freeze account", "unrecognized transactions", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a card payment I do not recognise."

Keyphrases:
1098it [29:35,  2.36s/it]
ChatCompletion(id='chatcmpl-9MyYGVIzGgaHy4Lc4U1i8sm30ndCV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "fraudulent charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715263004, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["unrecognized transaction", "fraudulent charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't recognise a card payment"

Keyphrases:
1099it [29:37,  2.28s/it]
ChatCompletion(id='chatcmpl-9MyYIA9g0s3OP8AQvks0VnA0tRqa5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "dispute transaction", "fraudulent charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715263006, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["unrecognized transaction", "dispute transaction", "fraudulent charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Payment i did not do"

Keyphrases:
1100it [29:41,  2.81s/it]
ChatCompletion(id='chatcmpl-9MyYK5Cxhi8OEz6gHconK9rDsgnwn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraudulent charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715263008, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=16, prompt_tokens=224, total_tokens=240))
["unauthorized transaction", "fraudulent charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please put a freeze on my card,  I am worried there has been some payments on it and I don't know what for."

Keyphrases:
1101it [29:43,  2.39s/it]
ChatCompletion(id='chatcmpl-9MyYOWph2l3ULn92iR3oXOdeyKVPQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card freeze", "suspicious transactions", "freeze account"]', role='assistant', function_call=None, tool_calls=None))], created=1715263012, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=245, total_tokens=259))
["card freeze", "suspicious transactions", "freeze account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think my statement has a fraudulent charge"

Keyphrases:
1102it [29:45,  2.28s/it]
ChatCompletion(id='chatcmpl-9MyYPjhT1rydDAmAsloxbLeLtI0JR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fraudulent charge", "dispute charge", "statement issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715263013, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["fraudulent charge", "dispute charge", "statement issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm concerned about a payment that has recently been made on my card.  I do not recognize the name that the transaction went to, can you help me?"

Keyphrases:
1103it [29:46,  1.99s/it]
ChatCompletion(id='chatcmpl-9MyYRuPUF9oSm5mV3o5L6CL50qOlR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "fraudulent payment", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715263015, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=251, total_tokens=266))
["unrecognized transaction", "fraudulent payment", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What should I do to get transactions off of my account if I didn't make them?  My card must have been compromised and I need to freeze it asap!"

Keyphrases:
1104it [29:47,  1.78s/it]
ChatCompletion(id='chatcmpl-9MyYSzjbblekvrjpaL9OHoHXcmatU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fraudulent transactions", "freeze card", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715263016, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=252, total_tokens=266))
["fraudulent transactions", "freeze card", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a payment listed in error."

Keyphrases:
1105it [29:49,  1.84s/it]
ChatCompletion(id='chatcmpl-9MyYUhARqJlThOEZX94BCUQqu2Z47', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment error", "incorrect charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715263018, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["payment error", "incorrect charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What can I do about some payments on my card I didn't make.  Please put a freeze on my card till we can figure this out."

Keyphrases:
1106it [29:51,  1.65s/it]
ChatCompletion(id='chatcmpl-9MyYWPji0UxUI6uto0aKw7YZrmFR5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transactions", "freeze card", "dispute charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715263020, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=248, total_tokens=262))
["unauthorized transactions", "freeze card", "dispute charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm not familiar with a card payment."

Keyphrases:
1107it [29:52,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyYXUdbqoFNCSRHNgjLCOK32pWp5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "dispute transaction", "unknown card payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715263021, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["unrecognized transaction", "dispute transaction", "unknown card payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have an unauthorized transaction on my statement"

Keyphrases:
1108it [29:54,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyYZKLeqjmGNZzvnUUM8dp6aAkja', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraudulent charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715263023, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["unauthorized transaction", "fraudulent charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a payment in the App that is not mine."

Keyphrases:
1109it [29:55,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyYakGZIwvPvlUdJp0n0MvUZ1W4b', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized payment", "fraudulent transaction", "payment dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715263024, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["unauthorized payment", "fraudulent transaction", "payment dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't know where this transaction came from?"

Keyphrases:
1110it [29:56,  1.44s/it]
ChatCompletion(id='chatcmpl-9MyYbUOipYZoQwZYOd4gigVqPlUCu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "fraudulent transaction", "transaction query"]', role='assistant', function_call=None, tool_calls=None))], created=1715263025, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["unrecognized transaction", "fraudulent transaction", "transaction query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I see a charge on my account that I don't recall making. I feel like my account may have been compromised."

Keyphrases:
1111it [29:58,  1.52s/it]
ChatCompletion(id='chatcmpl-9MyYdRtDJ6dYO6qla0tKW1jtjn4uc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized charge", "account security", "fraudulent transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715263027, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=242, total_tokens=257))
["unrecognized charge", "account security", "fraudulent transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I know I didn't make this payment showing up on my card, I don't remember this person at all."

Keyphrases:
1112it [30:00,  1.52s/it]
ChatCompletion(id='chatcmpl-9MyYeXwoQKwW8paMk9AcXjYJSoA5l', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fraudulent transaction", "unrecognized payment", "dispute charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715263028, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=241, total_tokens=257))
["fraudulent transaction", "unrecognized payment", "dispute charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Somebody used my card to make a purchase"

Keyphrases:
1113it [30:02,  1.67s/it]
ChatCompletion(id='chatcmpl-9MyYgxUjk5sGjDJgEzV7BeUR8wGPF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraudulent charge", "card security"]', role='assistant', function_call=None, tool_calls=None))], created=1715263030, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["unauthorized transaction", "fraudulent charge", "card security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There's a recent charge on my card that I know I didn't make because I've never seen the name before. Can we investigate this?"

Keyphrases:
1114it [30:03,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyYiQ7g3FhdOKvVszjR7MVmgZJuS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fraudulent charge", "unrecognized transaction", "transaction dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715263032, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=247, total_tokens=262))
["fraudulent charge", "unrecognized transaction", "transaction dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Some of my card payments look different than where I purchased products from. Why is that?"

Keyphrases:
1115it [30:05,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyYjTWCF1ZkSSpEZF9Mkulr6JBb1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment discrepancy", "mismatched transactions", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715263033, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["card payment discrepancy", "mismatched transactions", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a strange payment on my statement. What should I do?"

Keyphrases:
1116it [30:07,  1.89s/it]
ChatCompletion(id='chatcmpl-9MyYlmkmfplul2bj1Q6Z5pM0NbhPB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized payment", "dispute transaction", "fraudulent payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715263035, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["unauthorized payment", "dispute transaction", "fraudulent payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think there has been a purchase made that wasn't by me."

Keyphrases:
1117it [30:12,  2.88s/it]
ChatCompletion(id='chatcmpl-9MyYnsABZaexBCLP75xNFJ5F1WGtu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraudulent purchase", "transaction dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715263037, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["unauthorized transaction", "fraudulent purchase", "transaction dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a fraudulent charge on my statement."

Keyphrases:
1118it [30:15,  2.84s/it]
ChatCompletion(id='chatcmpl-9MyYtNzuDWWsYQAtIe1j0H2APBYKc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fraudulent charge", "dispute transaction", "report fraud"]', role='assistant', function_call=None, tool_calls=None))], created=1715263043, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["fraudulent charge", "dispute transaction", "report fraud"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the payment in my account that I did not do?"

Keyphrases:
1119it [30:20,  3.39s/it]
ChatCompletion(id='chatcmpl-9MyYv8NFoKq3smarjaObzfvSKZcJ0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized payment", "suspicious transaction", "payment query"]', role='assistant', function_call=None, tool_calls=None))], created=1715263045, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["unauthorized payment", "suspicious transaction", "payment query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "In my statement there is a payment that is I do not recognize"

Keyphrases:
1120it [30:23,  3.39s/it]
ChatCompletion(id='chatcmpl-9MyZ0Nxx6qJIurYGLi2sX3gbX4Ri9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized payment", "statement query", "fraudulent transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715263050, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["unrecognized payment", "statement query", "fraudulent transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I no longer live at my address on file, how do I change it?"

Keyphrases:
1121it [30:28,  3.69s/it]
ChatCompletion(id='chatcmpl-9MyZ43L86HWbKLu3QfShj8X54ncXC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update address", "change of address", "address modification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263054, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["update address", "change of address", "address modification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How to change my address."

Keyphrases:
1122it [30:29,  2.96s/it]
ChatCompletion(id='chatcmpl-9MyZ8xcXrzV8Zk7A37Wd22l1cH75X', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["address update", "change address", "update personal information"]', role='assistant', function_call=None, tool_calls=None))], created=1715263058, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["address update", "change address", "update personal information"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I update my details?"

Keyphrases:
1123it [30:30,  2.50s/it]
ChatCompletion(id='chatcmpl-9MyZ9wGjIxf2AFcopgUczYdXbfBwU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update personal details", "change account information", "modify user data"]', role='assistant', function_call=None, tool_calls=None))], created=1715263059, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["update personal details", "change account information", "modify user data"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My address needs to be revised."

Keyphrases:
1124it [30:32,  2.19s/it]
ChatCompletion(id='chatcmpl-9MyZB3XVLdY7MM58JL63Kzj7KEzDR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update address", "change address details", "address revision"]', role='assistant', function_call=None, tool_calls=None))], created=1715263061, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["update address", "change address details", "address revision"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "got married, need to change account name"

Keyphrases:
1125it [30:33,  2.00s/it]
ChatCompletion(id='chatcmpl-9MyZCURzqMiItaE73EMXGSAxaOvdx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["name change", "update personal information", "marriage name change"]', role='assistant', function_call=None, tool_calls=None))], created=1715263062, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["name change", "update personal information", "marriage name change"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My address has changed."

Keyphrases:
1126it [30:35,  2.03s/it]
ChatCompletion(id='chatcmpl-9MyZEoyR8Rjr4Kw9BG6fbGPfpEIRj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update address", "change of address", "address modification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263064, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["update address", "change of address", "address modification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "got married and need to change name"

Keyphrases:
1127it [30:37,  1.88s/it]
ChatCompletion(id='chatcmpl-9MyZGT74VwwDKmjy1ker9N85d7xUr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["name change", "update personal information", "marital status change"]', role='assistant', function_call=None, tool_calls=None))], created=1715263066, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["name change", "update personal information", "marital status change"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to change my personal details."

Keyphrases:
1128it [30:38,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyZHr1RtimtO6CwbIRT7axIcblgM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update personal details", "change personal information", "modify account details"]', role='assistant', function_call=None, tool_calls=None))], created=1715263067, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["update personal details", "change personal information", "modify account details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I moved.  I need to update my details."

Keyphrases:
1129it [30:39,  1.58s/it]
ChatCompletion(id='chatcmpl-9MyZI6XKGyoowuhfD1UTlhvNS8mVy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update personal details", "change address", "profile update"]', role='assistant', function_call=None, tool_calls=None))], created=1715263068, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["update personal details", "change address", "profile update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to edit the personal details section of my account"

Keyphrases:
1130it [30:41,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyZK1sCqgzjR9wQEVc2JY5JGmiaW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["edit personal details", "update account information", "modify user data"]', role='assistant', function_call=None, tool_calls=None))], created=1715263070, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["edit personal details", "update account information", "modify user data"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I change my personal information after I move?"

Keyphrases:
1131it [30:45,  2.31s/it]
ChatCompletion(id='chatcmpl-9MyZLniRSdvhgbu0b0L4obXppdzet', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update personal information", "change address", "profile update"]', role='assistant', function_call=None, tool_calls=None))], created=1715263071, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["update personal information", "change address", "profile update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I go to modify my detail?"

Keyphrases:
1132it [30:49,  2.91s/it]
ChatCompletion(id='chatcmpl-9MyZPDIzNDVEYInqqOKXy5ziw6YTI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["profile update", "modify personal information", "update account details"]', role='assistant', function_call=None, tool_calls=None))], created=1715263075, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["profile update", "modify personal information", "update account details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I change my information?"

Keyphrases:
1133it [30:50,  2.38s/it]
ChatCompletion(id='chatcmpl-9MyZTpVqtoIs0ixoTjanZ5hxooRRy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update personal information", "change account details", "modify user data"]', role='assistant', function_call=None, tool_calls=None))], created=1715263079, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["update personal information", "change account details", "modify user data"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to change my account details"

Keyphrases:
1134it [30:52,  2.06s/it]
ChatCompletion(id='chatcmpl-9MyZVCAEXwhdDuPHza11b8TBPm1Pp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update account details", "change personal information", "modify account settings"]', role='assistant', function_call=None, tool_calls=None))], created=1715263081, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["update account details", "change personal information", "modify account settings"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I moved.  Where do I update my details?"

Keyphrases:
1135it [30:53,  1.87s/it]
ChatCompletion(id='chatcmpl-9MyZWuCZHkB13qV6GfgSceH7XxnEX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update address", "change of address", "personal details update"]', role='assistant', function_call=None, tool_calls=None))], created=1715263082, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["update address", "change of address", "personal details update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I relocated and need to change my personal details."

Keyphrases:
1136it [30:54,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyZXqPlSq42w5cQoVHdsfcPel8PJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update personal details", "change address", "modify account information"]', role='assistant', function_call=None, tool_calls=None))], created=1715263083, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["update personal details", "change address", "modify account information"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to update my personal details"

Keyphrases:
1137it [30:56,  1.67s/it]
ChatCompletion(id='chatcmpl-9MyZZGbTNhbKlC8hdZGk4vHVWrR8j', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update personal details", "change of information", "profile update"]', role='assistant', function_call=None, tool_calls=None))], created=1715263085, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["update personal details", "change of information", "profile update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My address has changed. How do I report it?"

Keyphrases:
1138it [30:59,  2.21s/it]
ChatCompletion(id='chatcmpl-9MyZbNnK2qFV1cm6C2v64qlxEquiL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update address", "change of address", "address modification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263087, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["update address", "change of address", "address modification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to update my info."

Keyphrases:
1139it [31:01,  2.14s/it]
ChatCompletion(id='chatcmpl-9MyZeKNjwdSLxZ8QEzLCLnSMpv14W', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update personal information", "change account details", "modify user data"]', role='assistant', function_call=None, tool_calls=None))], created=1715263090, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["update personal information", "change account details", "modify user data"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I modify my details?"

Keyphrases:
1140it [31:04,  2.22s/it]
ChatCompletion(id='chatcmpl-9MyZgKNpuD4YAuVJ0snZX5uHUBAcc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update personal information", "modify account details", "change user info"]', role='assistant', function_call=None, tool_calls=None))], created=1715263092, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["update personal information", "modify account details", "change user info"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do i have to do to change my name?"

Keyphrases:
1141it [31:05,  1.94s/it]
ChatCompletion(id='chatcmpl-9MyZiL0cq1VR5L7rIo3lvokMOZo46', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["name change", "personal information update", "update account details"]', role='assistant', function_call=None, tool_calls=None))], created=1715263094, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["name change", "personal information update", "update account details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My address has updated and I need to change it."

Keyphrases:
1142it [31:07,  2.03s/it]
ChatCompletion(id='chatcmpl-9MyZjlx4hzuDAM75O05b1tkcrxNUY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update address", "change address", "address modification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263095, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["update address", "change address", "address modification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I go to update my personal profile?"

Keyphrases:
1143it [31:11,  2.51s/it]
ChatCompletion(id='chatcmpl-9MyZmzyY1EWcKvtQ9A9vazVadxH8D', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["profile update", "update personal information", "edit profile"]', role='assistant', function_call=None, tool_calls=None))], created=1715263098, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["profile update", "update personal information", "edit profile"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to edit my personal details on the app?"

Keyphrases:
1144it [31:13,  2.29s/it]
ChatCompletion(id='chatcmpl-9MyZptXnhjXNzIz8Y7h1e4hccAsz6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["edit personal details", "update profile information", "modify user data"]', role='assistant', function_call=None, tool_calls=None))], created=1715263101, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["edit personal details", "update profile information", "modify user data"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how can i change my details"

Keyphrases:
1145it [31:14,  2.05s/it]
ChatCompletion(id='chatcmpl-9MyZrYaujvIKPN3UGfUefrLTbMhrG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update personal information", "change account details", "modify user data"]', role='assistant', function_call=None, tool_calls=None))], created=1715263103, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["update personal information", "change account details", "modify user data"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need help changing my last name on my account."

Keyphrases:
1146it [31:16,  1.89s/it]
ChatCompletion(id='chatcmpl-9MyZtUC70r2T5iNnUkyO3D56CKdv1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["name change", "update account information", "change last name"]', role='assistant', function_call=None, tool_calls=None))], created=1715263105, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["name change", "update account information", "change last name"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I update my current residence details?"

Keyphrases:
1147it [31:18,  1.87s/it]
ChatCompletion(id='chatcmpl-9MyZuLPHEvgGyy23G7ntf75MAGDdS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update residence information", "change address", "address modification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263106, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["update residence information", "change address", "address modification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how do i change name?"

Keyphrases:
1148it [31:19,  1.73s/it]
ChatCompletion(id='chatcmpl-9MyZw1UaeKPPVHVNxJtwckAMuxWMa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["name change", "update personal information", "modify account name"]', role='assistant', function_call=None, tool_calls=None))], created=1715263108, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["name change", "update personal information", "modify account name"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to change my name since I got married"

Keyphrases:
1149it [31:21,  1.82s/it]
ChatCompletion(id='chatcmpl-9MyZx5TmkdqF79t8NEwa9qaDyGxto', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["name change", "update personal information", "marriage name change"]', role='assistant', function_call=None, tool_calls=None))], created=1715263109, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["name change", "update personal information", "marriage name change"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to change my address."

Keyphrases:
1150it [31:23,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyZzgWLguV3dQCMWjvDxdoAVHsLj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update address", "change of address", "address modification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263111, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["update address", "change of address", "address modification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how to change name"

Keyphrases:
1151it [41:25, 181.85s/it]
ChatCompletion(id='chatcmpl-9Myjivv566wtQRZpjQCqxZq0d7AUM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["name change", "update personal information", "modify account name"]', role='assistant', function_call=None, tool_calls=None))], created=1715263714, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=223, total_tokens=237))
["name change", "update personal information", "modify account name"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I change my information?"

Keyphrases:
1152it [41:27, 127.85s/it]
ChatCompletion(id='chatcmpl-9Myjj2nPyKhBYKrdgGm2FjHQ6aHDn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update personal information", "change account details", "modify user data"]', role='assistant', function_call=None, tool_calls=None))], created=1715263715, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["update personal information", "change account details", "modify user data"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to update my current address"

Keyphrases:
1153it [41:28, 89.92s/it] 
ChatCompletion(id='chatcmpl-9Myjl2FVye3ACTt21u5F1rxijPZh2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update address", "change of address", "address modification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263717, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["update address", "change of address", "address modification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have moved.  Where can I update my details?"

Keyphrases:
1154it [41:32, 64.04s/it]
ChatCompletion(id='chatcmpl-9MyjmIaR3BjJqP3cMTiFaMrWzpf2k', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update personal details", "change address", "edit profile information"]', role='assistant', function_call=None, tool_calls=None))], created=1715263718, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["update personal details", "change address", "edit profile information"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to change my name."

Keyphrases:
1155it [41:33, 45.28s/it]
ChatCompletion(id='chatcmpl-9MyjqetgRbyn6NdiY5YzDAnK7jSVl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["name change", "update personal information", "modify account details"]', role='assistant', function_call=None, tool_calls=None))], created=1715263722, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["name change", "update personal information", "modify account details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Should I just wait until the post office sends a change of address form?"

Keyphrases:
1156it [41:35, 32.28s/it]
ChatCompletion(id='chatcmpl-9MyjrNEniNmOx4mC6ofJH707h47HO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["postal change of address", "waiting for address form", "post office procedures"]', role='assistant', function_call=None, tool_calls=None))], created=1715263723, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=233, total_tokens=250))
["postal change of address", "waiting for address form", "post office procedures"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to change my name what do I do?"

Keyphrases:
1157it [41:37, 23.07s/it]
ChatCompletion(id='chatcmpl-9Myjtd4BSu5CLznLn9Xp73FODTZaB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["name change", "update personal information", "change account name"]', role='assistant', function_call=None, tool_calls=None))], created=1715263725, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["name change", "update personal information", "change account name"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I edit my personal details?"

Keyphrases:
1158it [41:39, 16.86s/it]
ChatCompletion(id='chatcmpl-9Myjvt5zUyrQkUG6KYup41g9s6FoN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["edit personal details", "update information", "change account details"]', role='assistant', function_call=None, tool_calls=None))], created=1715263727, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["edit personal details", "update information", "change account details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I change my address?"

Keyphrases:
1159it [41:41, 12.51s/it]
ChatCompletion(id='chatcmpl-9MyjxtkU3eFK55lkdxIxgjQrHNvqK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update address", "change contact details", "address modification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263729, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["update address", "change contact details", "address modification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I need to do to change the address on my account?"

Keyphrases:
1160it [41:43,  9.12s/it]
ChatCompletion(id='chatcmpl-9Myk0BKvyzx07BqbnpXM26BuqMxqt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["address change", "update address", "change account information"]', role='assistant', function_call=None, tool_calls=None))], created=1715263732, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["address change", "update address", "change account information"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do you require so many details about my identity?"

Keyphrases:
1161it [41:44,  6.69s/it]
ChatCompletion(id='chatcmpl-9Myk1DXtQrebTE7WsgS2m1lZQzGD6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC requirements", "personal details"]', role='assistant', function_call=None, tool_calls=None))], created=1715263733, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["identity verification", "KYC requirements", "personal details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'd rather not verify my identity."

Keyphrases:
1162it [41:45,  5.09s/it]
ChatCompletion(id='chatcmpl-9Myk2aMdPBT09XHqpKSWQI8Nzuol1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "skip verification", "verification refusal"]', role='assistant', function_call=None, tool_calls=None))], created=1715263734, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["identity verification", "skip verification", "verification refusal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "do I need to verify my identity every time I log into my account?"

Keyphrases:
1163it [41:46,  3.88s/it]
ChatCompletion(id='chatcmpl-9Myk3XBV6Al92GbZmbio8VxFtDnwQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "account security", "login requirements"]', role='assistant', function_call=None, tool_calls=None))], created=1715263735, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=233, total_tokens=245))
["identity verification", "account security", "login requirements"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why am I required to verify my identity?"

Keyphrases:
1164it [41:47,  3.10s/it]
ChatCompletion(id='chatcmpl-9Myk4IYoD5yhyUL9JJplp3GCCA2wJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "security procedure", "KYC compliance"]', role='assistant', function_call=None, tool_calls=None))], created=1715263736, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "security procedure", "KYC compliance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I make transfers before identity verification?"

Keyphrases:
1165it [41:49,  2.60s/it]
ChatCompletion(id='chatcmpl-9Myk6wrV3SFaaXLqRg3LxYSFh9XuF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pre-verification transfers", "identity verification requirement", "transfer rules before verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263738, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["pre-verification transfers", "identity verification requirement", "transfer rules before verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the need to verify my identity?"

Keyphrases:
1166it [41:50,  2.20s/it]
ChatCompletion(id='chatcmpl-9Myk7srfOBKMdUYTLKaXEqOSqvJS2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification requirement", "KYC process"]', role='assistant', function_call=None, tool_calls=None))], created=1715263739, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "verification requirement", "KYC process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I have to do the identity check?"

Keyphrases:
1167it [41:51,  1.95s/it]
ChatCompletion(id='chatcmpl-9Myk8NhmxIVyEqiTUBaFTleYZaCNo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC process", "verification requirement"]', role='assistant', function_call=None, tool_calls=None))], created=1715263740, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "KYC process", "verification requirement"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use my account without verifying my identity?"

Keyphrases:
1168it [41:53,  1.87s/it]
ChatCompletion(id='chatcmpl-9MykAIsdguHnRO7MS6uu1nC5qp0t7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "account usage without verification", "unverified account access"]', role='assistant', function_call=None, tool_calls=None))], created=1715263742, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["identity verification", "account usage without verification", "unverified account access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is identity verification mandatory?"

Keyphrases:
1169it [41:54,  1.69s/it]
ChatCompletion(id='chatcmpl-9MykB05YJRT0rGLnwvUqsLUtVMsjQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification requirement", "mandatory verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263743, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["identity verification", "verification requirement", "mandatory verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I have to do an identity check?"

Keyphrases:
1170it [41:56,  1.53s/it]
ChatCompletion(id='chatcmpl-9MykDsNE6hj6AvW4fu88i40r4MoBZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC", "mandatory identity check"]', role='assistant', function_call=None, tool_calls=None))], created=1715263745, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "KYC", "mandatory identity check"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to not have to do the identity verification."

Keyphrases:
1171it [41:57,  1.47s/it]
ChatCompletion(id='chatcmpl-9MykEC2Xx1EcAQ4BKmdMAcouNHXWM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bypass identity verification", "skip verification", "no ID check"]', role='assistant', function_call=None, tool_calls=None))], created=1715263746, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["bypass identity verification", "skip verification", "no ID check"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I still use my account, even though the identity verification has not passed yet?"

Keyphrases:
1172it [41:58,  1.39s/it]
ChatCompletion(id='chatcmpl-9MykFTuFFMSEZkiTEOCfRVBXO4N7g', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account access", "identity verification pending", "use account without verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263747, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=235, total_tokens=250))
["account access", "identity verification pending", "use account without verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do you require all my identity details?"

Keyphrases:
1173it [42:01,  1.90s/it]
ChatCompletion(id='chatcmpl-9MykGUn8CvHMgvxfaVUKbkBRri3ao', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC requirements", "privacy policy"]', role='assistant', function_call=None, tool_calls=None))], created=1715263748, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "KYC requirements", "privacy policy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do you need so much information to verify my identity?"

Keyphrases:
1174it [42:03,  1.82s/it]
ChatCompletion(id='chatcmpl-9MykJnA9ABki94IwLA4SPz9DA9wFJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification requirements", "KYC process"]', role='assistant', function_call=None, tool_calls=None))], created=1715263751, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["identity verification", "verification requirements", "KYC process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the purpose for the identity check"

Keyphrases:
1175it [42:05,  1.94s/it]
ChatCompletion(id='chatcmpl-9MykLkWs1g2fjc6UGAwlyNPZOpc0t', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC process", "verification purpose"]', role='assistant', function_call=None, tool_calls=None))], created=1715263753, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "KYC process", "verification purpose"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't like that I have to fill out so much information about my identity."

Keyphrases:
1176it [42:07,  1.84s/it]
ChatCompletion(id='chatcmpl-9MykNhbnDlS5ymiJbcoTnCbVvIWGf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification complaints", "excessive identity information", "user dissatisfaction identity verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263755, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=235, total_tokens=252))
["identity verification complaints", "excessive identity information", "user dissatisfaction identity verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the point of an identity check?"

Keyphrases:
1177it [42:08,  1.82s/it]
ChatCompletion(id='chatcmpl-9MykPDka7Pxj1qnKZKgjYT7L0KeZO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification purpose", "KYC importance", "reason for identity check"]', role='assistant', function_call=None, tool_calls=None))], created=1715263757, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["identity verification purpose", "KYC importance", "reason for identity check"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How come you need to know my identity?"

Keyphrases:
1178it [42:10,  1.84s/it]
ChatCompletion(id='chatcmpl-9MykR0Hhk0yjhjf5HEniHfKEd8ZIg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC", "security protocol"]', role='assistant', function_call=None, tool_calls=None))], created=1715263759, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["identity verification", "KYC", "security protocol"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "May I use my account now, even though the identity verification has not gone through yet?"

Keyphrases:
1179it [42:12,  1.81s/it]
ChatCompletion(id='chatcmpl-9MykTRtPjkTmFCdNgMGZ3HNlQPHlV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account access", "identity verification pending", "pre-verification access"]', role='assistant', function_call=None, tool_calls=None))], created=1715263761, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["account access", "identity verification pending", "pre-verification access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I need to verify my identity to use my account?"

Keyphrases:
1180it [42:13,  1.61s/it]
ChatCompletion(id='chatcmpl-9MykUwBICbfmU79wMO1R64Z0pDGbo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "account security", "verification requirement"]', role='assistant', function_call=None, tool_calls=None))], created=1715263762, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["identity verification", "account security", "verification requirement"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why am I required to do an identity check?"

Keyphrases:
1181it [42:14,  1.52s/it]
ChatCompletion(id='chatcmpl-9MykVXLr0qYrjNjHvTqCzSyyL0six', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC process", "mandatory identity check"]', role='assistant', function_call=None, tool_calls=None))], created=1715263763, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["identity verification", "KYC process", "mandatory identity check"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why am I being asked to have an identity check"

Keyphrases:
1182it [42:16,  1.40s/it]
ChatCompletion(id='chatcmpl-9MykXfSX7osoZcllMTFCUKPoqnZLv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "security check", "KYC process"]', role='assistant', function_call=None, tool_calls=None))], created=1715263765, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["identity verification", "security check", "KYC process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can i make transactions before identity verification is complete?"

Keyphrases:
1183it [42:17,  1.55s/it]
ChatCompletion(id='chatcmpl-9MykYUcaUqkek0WVk6rKe2d4GrB3K', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pre-verification transactions", "identity verification", "transaction eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715263766, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["pre-verification transactions", "identity verification", "transaction eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I really need to verify my identity?"

Keyphrases:
1184it [42:20,  1.75s/it]
ChatCompletion(id='chatcmpl-9MykaELFY5AnmpUkJkx1lsEFPCZha', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification requirement", "KYC process"]', role='assistant', function_call=None, tool_calls=None))], created=1715263768, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "verification requirement", "KYC process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do I have to give you all of my identification details?"

Keyphrases:
1185it [42:23,  2.07s/it]
ChatCompletion(id='chatcmpl-9MykcQwKjuzrfhBt4WyzaebtLiHlr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC requirements", "compliance policy"]', role='assistant', function_call=None, tool_calls=None))], created=1715263770, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["identity verification", "KYC requirements", "compliance policy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do you require so many identity details?"

Keyphrases:
1186it [42:24,  1.96s/it]
ChatCompletion(id='chatcmpl-9MykfveiTvHiWqE6DY38l5glflpAK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC requirements", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715263773, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "KYC requirements", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Since my id hasn't been verified, when can I use my account?"

Keyphrases:
1187it [42:27,  2.06s/it]
ChatCompletion(id='chatcmpl-9MykhYzPFe2Abqtr2pC05Y4orYQup', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account verification", "verification status", "account access post-verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263775, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["account verification", "verification status", "account access post-verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I won't verify my identity."

Keyphrases:
1188it [42:29,  2.28s/it]
ChatCompletion(id='chatcmpl-9MykjE3FcZL9IfeSYCOeEtbaoJvMx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification refusal", "reject identity verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263777, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=10, prompt_tokens=225, total_tokens=235))
["identity verification refusal", "reject identity verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to skip verification of my identity."

Keyphrases:
1189it [42:31,  1.96s/it]
ChatCompletion(id='chatcmpl-9MykmHmP1O8tzNdmyOJ7Y5jtqCXxa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["skip identity verification", "bypass KYC", "avoid identity check"]', role='assistant', function_call=None, tool_calls=None))], created=1715263780, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["skip identity verification", "bypass KYC", "avoid identity check"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I do not wish to verify my identity."

Keyphrases:
1190it [42:32,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyknhMjgMxWuqdTkg7ovxbryctv0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification refusal", "skip identity verification", "reject identity verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263781, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["identity verification refusal", "skip identity verification", "reject identity verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do I have to verify my identity?"

Keyphrases:
1191it [42:33,  1.64s/it]
ChatCompletion(id='chatcmpl-9MykoLuWzOLdYQwJheixjrjtSN8aV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification requirement", "KYC compliance"]', role='assistant', function_call=None, tool_calls=None))], created=1715263782, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "verification requirement", "KYC compliance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what is the identity check?"

Keyphrases:
1192it [42:35,  1.61s/it]
ChatCompletion(id='chatcmpl-9MykqVOxJlHfRvqgfDbd08G3tF601', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC process", "account security check"]', role='assistant', function_call=None, tool_calls=None))], created=1715263784, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["identity verification", "KYC process", "account security check"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What other methods are there to verify my identity?"

Keyphrases:
1193it [42:37,  1.71s/it]
ChatCompletion(id='chatcmpl-9MykrBkvxdINqds6Ghw1NT13xJcXH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification methods", "alternative verification", "verification options"]', role='assistant', function_call=None, tool_calls=None))], created=1715263785, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["identity verification methods", "alternative verification", "verification options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I need to verify my identity?"

Keyphrases:
1194it [42:38,  1.56s/it]
ChatCompletion(id='chatcmpl-9Myktl4ebD33yUcbS6rqwgAJCRX49', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC requirements", "account verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263787, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["identity verification", "KYC requirements", "account verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I need to verify my identity each time I wish to use my account?"

Keyphrases:
1195it [42:40,  1.74s/it]
ChatCompletion(id='chatcmpl-9MykuSuA9o52lvXBB9liZzjsCVxLb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "account security", "verification frequency"]', role='assistant', function_call=None, tool_calls=None))], created=1715263788, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=234, total_tokens=246))
["identity verification", "account security", "verification frequency"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use my account if the identity verification is not complete?"

Keyphrases:
1196it [42:42,  1.77s/it]
ChatCompletion(id='chatcmpl-9MykwJyK0JQxXFU77xEOW2me9HdHy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification status", "account access restrictions", "incomplete verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263790, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["identity verification status", "account access restrictions", "incomplete verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is it asking me to verify my identity"

Keyphrases:
1197it [42:43,  1.66s/it]
ChatCompletion(id='chatcmpl-9MykyUf8Abj32XtxzJ92AAt1FuzZi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "account security", "verification required"]', role='assistant', function_call=None, tool_calls=None))], created=1715263792, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["identity verification", "account security", "verification required"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I have to verify my identity?"

Keyphrases:
1198it [42:45,  1.66s/it]
ChatCompletion(id='chatcmpl-9Myl0kGswaE4NzQxdZ5Faraa5fysJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC requirements", "verification process"]', role='assistant', function_call=None, tool_calls=None))], created=1715263794, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["identity verification", "KYC requirements", "verification process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do you need to know so much about me"

Keyphrases:
1199it [42:47,  1.63s/it]
ChatCompletion(id='chatcmpl-9Myl18xDCpsiYrLIRw2MgKzAcv4dY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["privacy policy", "information requirement", "data usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715263795, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["privacy policy", "information requirement", "data usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I need to verfiy my identity?"

Keyphrases:
1200it [42:48,  1.54s/it]
ChatCompletion(id='chatcmpl-9Myl3UqWyGUp0NAURNeX1ebKW1BsY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification requirement", "KYC process"]', role='assistant', function_call=None, tool_calls=None))], created=1715263797, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["identity verification", "verification requirement", "KYC process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I cannot verify my identity"

Keyphrases:
1201it [42:49,  1.51s/it]
ChatCompletion(id='chatcmpl-9Myl4M14Xw5W9kFJksiCMRQk5dHvj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification issue", "authentication problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715263798, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["identity verification", "verification issue", "authentication problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I do not have what is required to prove my identity"

Keyphrases:
1202it [42:51,  1.44s/it]
ChatCompletion(id='chatcmpl-9Myl609CMGkTMAXH9j2UFUS61brXc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "lack of identification", "verification issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715263800, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["identity verification", "lack of identification", "verification issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why doesn't the app believe I am who I say I am?"

Keyphrases:
1203it [42:53,  1.67s/it]
ChatCompletion(id='chatcmpl-9Myl7LgPpDhdgn5rQv3WvJyZwMENs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "authentication issue", "login problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715263801, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["identity verification", "authentication issue", "login problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am having trouble verifying my identity."

Keyphrases:
1204it [42:54,  1.51s/it]
ChatCompletion(id='chatcmpl-9Myl9ngR4299jBlkyENO8jdF11MgZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification issue", "account verification problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715263803, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["identity verification", "verification issue", "account verification problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what do i do if my verification failed"

Keyphrases:
1205it [42:56,  1.76s/it]
ChatCompletion(id='chatcmpl-9MylAHjJj5WT5kuZ5jaPi4aCOqlyx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification issue", "failed verification", "account verification problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715263804, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["verification issue", "failed verification", "account verification problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It is impossible to verify my identity"

Keyphrases:
1206it [42:57,  1.56s/it]
ChatCompletion(id='chatcmpl-9MylDUA5SOpXbGSZu8Fa1bLQigtC2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification issue", "cannot verify identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715263807, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["identity verification", "verification issue", "cannot verify identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app doesn't know it's me."

Keyphrases:
1207it [42:59,  1.50s/it]
ChatCompletion(id='chatcmpl-9MylEbfWKS12eLD5pKm261pu9m9U2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "app login issue", "recognition problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715263808, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["identity verification", "app login issue", "recognition problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm having trouble verifying my ID."

Keyphrases:
1208it [43:00,  1.45s/it]
ChatCompletion(id='chatcmpl-9MylFGrZv8jewdmwgZvyIu9OeHcY6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification issue", "verification problem", "identity confirmation"]', role='assistant', function_call=None, tool_calls=None))], created=1715263809, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["ID verification issue", "verification problem", "identity confirmation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "app does not recognize me"

Keyphrases:
1209it [43:02,  1.46s/it]
ChatCompletion(id='chatcmpl-9MylHxmC7ZTZXeAMCIMT1SyjX7IC9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["login issue", "authentication problem", "app recognition failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715263811, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["login issue", "authentication problem", "app recognition failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help my verify my id."

Keyphrases:
1210it [43:05,  2.04s/it]
ChatCompletion(id='chatcmpl-9MylIMDvU9cLlsFLQZ9iEK9u9wmRj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification", "verify identity", "account verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263812, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["ID verification", "verify identity", "account verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app failed to verify my identity."

Keyphrases:
1211it [43:06,  1.87s/it]
ChatCompletion(id='chatcmpl-9MylLbcPdQ6FzCmVIIOw9UzZ0rC6w', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification issue", "app failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715263815, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["identity verification", "verification issue", "app failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't verify my ID."

Keyphrases:
1212it [43:10,  2.26s/it]
ChatCompletion(id='chatcmpl-9MylNfImlsW70CFcGPVJ8KDyBL0UA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification", "verification issue", "identity confirmation"]', role='assistant', function_call=None, tool_calls=None))], created=1715263817, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["ID verification", "verification issue", "identity confirmation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't prove my identity."

Keyphrases:
1213it [43:11,  1.92s/it]
ChatCompletion(id='chatcmpl-9MylQ7MoEf2YB6A3qUQV4xrnsLICO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification issue", "cannot verify identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715263820, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["identity verification", "verification issue", "cannot verify identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am not being recognized by the app."

Keyphrases:
1214it [43:12,  1.77s/it]
ChatCompletion(id='chatcmpl-9MylROoHLULj8LaaZQDRsw5GGVjuA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["authentication issue", "app login problem", "user recognition failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715263821, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["authentication issue", "app login problem", "user recognition failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why isn't my ID being verified?"

Keyphrases:
1215it [43:15,  1.99s/it]
ChatCompletion(id='chatcmpl-9MylSr1QLTGTeSabP8Cz2vicveVvl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification", "verification issue", "account verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263822, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["ID verification", "verification issue", "account verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app will not let me into my account."

Keyphrases:
1216it [43:16,  1.73s/it]
ChatCompletion(id='chatcmpl-9MylVSyqjqCB8V2Hayrh3X2akxaek', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["app login issue", "account access problem", "login failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715263825, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["app login issue", "account access problem", "login failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am having trouble proving my identity."

Keyphrases:
1217it [43:17,  1.58s/it]
ChatCompletion(id='chatcmpl-9MylWw7Sj1kyKNq7Tnjl171mqjCUS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification issue", "prove identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715263826, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["identity verification", "verification issue", "prove identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I cannot prove my own identity."

Keyphrases:
1218it [43:18,  1.49s/it]
ChatCompletion(id='chatcmpl-9MylXDLhJ3HLkbgA7wTCBzVaiBcRB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification issue", "cannot verify identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715263827, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["identity verification", "verification issue", "cannot verify identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My ID won't be verified!"

Keyphrases:
1219it [43:20,  1.56s/it]
ChatCompletion(id='chatcmpl-9MylZtVQGD9gG7U6uu9pw0CZgeGSQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification", "verification issue", "account verification problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715263829, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["ID verification", "verification issue", "account verification problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can not get the app to know it is me."

Keyphrases:
1220it [43:22,  1.62s/it]
ChatCompletion(id='chatcmpl-9MylapOaaYGauElLf5iFdZcSSUtt1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["app authentication", "identity verification", "login issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715263830, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["app authentication", "identity verification", "login issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't verify my identity."

Keyphrases:
1221it [43:23,  1.48s/it]
ChatCompletion(id='chatcmpl-9MylcuLdxDq6GltxCG3Zuedohr2ZW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification issue", "cannot verify identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715263832, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["identity verification", "verification issue", "cannot verify identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app doesn't recognize me."

Keyphrases:
1222it [43:25,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyldaYlncj6ERjvwmFba0ub2Q5A8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["authentication issue", "login problem", "app access issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715263833, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["authentication issue", "login problem", "app access issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am having difficulties to verify my identity."

Keyphrases:
1223it [43:26,  1.49s/it]
ChatCompletion(id='chatcmpl-9MylfL9fRSOFT1280KzrDTCzbuFLv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification issues", "account verification problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715263835, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "verification issues", "account verification problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app doesn't believe that I am me"

Keyphrases:
1224it [43:28,  1.61s/it]
ChatCompletion(id='chatcmpl-9MylgtjESjNH3aVrZUHCtkkeCS6ub', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "authentication issue", "login problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715263836, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["identity verification", "authentication issue", "login problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What's with not verifying my Id?"

Keyphrases:
1225it [43:32,  2.26s/it]
ChatCompletion(id='chatcmpl-9MyliEjzoh5IamBTLejvVMWRgGFBW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification", "verification issue", "account verification problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715263838, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["ID verification", "verification issue", "account verification problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do i need to verify my id?"

Keyphrases:
1226it [43:33,  1.99s/it]
ChatCompletion(id='chatcmpl-9MylmmGH0wPj5TiZpADsvPnI6w7Eq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification requirements", "verify identity", "documentation for ID verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263842, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["ID verification requirements", "verify identity", "documentation for ID verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried verifying my ID, but it won't let me."

Keyphrases:
1227it [43:35,  1.86s/it]
ChatCompletion(id='chatcmpl-9Myln21a4awue995uzKNMaQwVUzJF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification issue", "verification problem", "account verification failed"]', role='assistant', function_call=None, tool_calls=None))], created=1715263843, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["ID verification issue", "verification problem", "account verification failed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I show this stupid system that this is really my identity?"

Keyphrases:
1228it [43:36,  1.65s/it]
ChatCompletion(id='chatcmpl-9MylpTNil69xWhQTCQXeX059gZzxj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "account authentication", "prove identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715263845, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["identity verification", "account authentication", "prove identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am experiencing difficulty providing my identity."

Keyphrases:
1229it [43:37,  1.51s/it]
ChatCompletion(id='chatcmpl-9Mylq2SqQbCaZEMTZA6XP5eNMMKDU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification issue", "identity confirmation problem", "verification difficulty"]', role='assistant', function_call=None, tool_calls=None))], created=1715263846, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["identity verification issue", "identity confirmation problem", "verification difficulty"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I a having trouble proving my identity"

Keyphrases:
1230it [43:38,  1.48s/it]
ChatCompletion(id='chatcmpl-9MylrgHyKIUjMc6OAsiPhPz75J3AC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification issue", "proof of identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715263847, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["identity verification", "verification issue", "proof of identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long will it take for my ID to verify?"

Keyphrases:
1231it [43:40,  1.59s/it]
ChatCompletion(id='chatcmpl-9Myltix1xhHSX5C2cWm8nV5EK3LOF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification time", "verification duration", "account verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263849, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["ID verification time", "verification duration", "account verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why am I not able to verify my id?"

Keyphrases:
1232it [43:42,  1.71s/it]
ChatCompletion(id='chatcmpl-9MyluLQLRwy3ZwCuPIuUhgMkr01ay', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification", "verification issue", "identity confirmation"]', role='assistant', function_call=None, tool_calls=None))], created=1715263850, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["ID verification", "verification issue", "identity confirmation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It doesn't let me verify my identity."

Keyphrases:
1233it [43:43,  1.50s/it]
ChatCompletion(id='chatcmpl-9Mylwizl7iv36oAnWQAW33Uao4TPE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification issue", "verification problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715263852, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=9, prompt_tokens=227, total_tokens=236))
["identity verification issue", "verification problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "app doesnt think its me"

Keyphrases:
1234it [43:47,  2.22s/it]
ChatCompletion(id='chatcmpl-9MylxNzzeVz226CObeyRdONcp4x7l', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["authentication issue", "identity verification", "login problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715263853, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["authentication issue", "identity verification", "login problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why am I having trouble verifying my id?"

Keyphrases:
1235it [43:49,  1.99s/it]
ChatCompletion(id='chatcmpl-9Mym1tCwb0Irr1KTJXtK3FFnByr8r', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification issue", "verification problem", "account verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715263857, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["ID verification issue", "verification problem", "account verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am having issues with identity verification"

Keyphrases:
1236it [43:50,  1.97s/it]
ChatCompletion(id='chatcmpl-9Mym3k36AHL9TtR2S86vVYbG77dOq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification issues", "account verification problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715263859, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["identity verification", "verification issues", "account verification problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app won't let me log in as myself."

Keyphrases:
1237it [43:53,  2.11s/it]
ChatCompletion(id='chatcmpl-9Mym5akilrfDamCM1LlsWqOu80L96', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["login issues", "app access problem", "authentication failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715263861, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["login issues", "app access problem", "authentication failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I verify my identity?"

Keyphrases:
1238it [43:54,  1.92s/it]
ChatCompletion(id='chatcmpl-9Mym7OoDoWUNr1KIGo6yMdJRFSWRG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification issue", "cannot verify identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715263863, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["identity verification", "verification issue", "cannot verify identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I verify my id?"

Keyphrases:
1239it [43:56,  1.89s/it]
ChatCompletion(id='chatcmpl-9Mym9slC47z3heFqe9JoVUBjgUNoR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification", "verification issue", "unable to verify identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715263865, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["ID verification", "verification issue", "unable to verify identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "for some reason I am having a problem with verifying my identity."

Keyphrases:
1240it [43:59,  2.32s/it]
ChatCompletion(id='chatcmpl-9MymA5ZBGQ8fSvg1wMFUejnSyiKnR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification issue", "account authentication problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715263866, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["identity verification", "verification issue", "account authentication problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do with my card PIN?"

Keyphrases:
1241it [44:02,  2.24s/it]
ChatCompletion(id='chatcmpl-9MymEwthE6bf2mrjTBfpId9AIUHF9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN management", "change PIN", "reset PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715263870, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["PIN management", "change PIN", "reset PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is the PIN delivered separately?"

Keyphrases:
1242it [44:04,  2.32s/it]
ChatCompletion(id='chatcmpl-9MymGFq0BOrrR2VQAHXu0b68ZrjbK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN delivery", "separate PIN delivery", "PIN shipment status"]', role='assistant', function_call=None, tool_calls=None))], created=1715263872, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["PIN delivery", "separate PIN delivery", "PIN shipment status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I do not have my pin"

Keyphrases:
1243it [44:06,  2.15s/it]
ChatCompletion(id='chatcmpl-9MymIGBVny6qhx3V0E9LYsS2NAWaw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing pin", "pin retrieval", "reset pin"]', role='assistant', function_call=None, tool_calls=None))], created=1715263874, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["missing pin", "pin retrieval", "reset pin"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are PIN separately?"

Keyphrases:
1244it [44:07,  1.99s/it]
ChatCompletion(id='chatcmpl-9MymKhboRwDdTGbO1uG9g0SRPTIDQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN delivery", "separate PIN", "PIN issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715263876, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=222, total_tokens=235))
["PIN delivery", "separate PIN", "PIN issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I cannot seem to find my PIN. Where is it?"

Keyphrases:
1245it [44:09,  1.75s/it]
ChatCompletion(id='chatcmpl-9MymMojZ6nHsz0rn9pW1v6OvQo3uZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN retrieval", "forgotten PIN", "locate PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715263878, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["PIN retrieval", "forgotten PIN", "locate PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I set-up my PIN for the new card?"

Keyphrases:
1246it [44:10,  1.60s/it]
ChatCompletion(id='chatcmpl-9MymNX9LjlCK2AybEWqo0jjbUJKqg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN setup", "new card PIN", "activate PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715263879, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["PIN setup", "new card PIN", "activate PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I find my card PIN?"

Keyphrases:
1247it [44:11,  1.51s/it]
ChatCompletion(id='chatcmpl-9MymOr2zdUVcL98mZVyAfqWnPU3FZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card PIN", "retrieve PIN", "PIN recovery"]', role='assistant', function_call=None, tool_calls=None))], created=1715263880, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["card PIN", "retrieve PIN", "PIN recovery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "is my card PIN saved in the app"

Keyphrases:
1248it [44:13,  1.48s/it]
ChatCompletion(id='chatcmpl-9MymPsmlJPJcPNnvnKdV7cWUKwH8i', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card PIN", "PIN storage", "security settings"]', role='assistant', function_call=None, tool_calls=None))], created=1715263881, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["card PIN", "PIN storage", "security settings"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't know where to look to find my PIN."

Keyphrases:
1249it [44:14,  1.39s/it]
ChatCompletion(id='chatcmpl-9MymRXNLOpmemznwo7fpeC92AfMa5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN retrieval", "find PIN", "PIN location"]', role='assistant', function_call=None, tool_calls=None))], created=1715263883, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["PIN retrieval", "find PIN", "PIN location"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "where in the app can i find out about my new pin"

Keyphrases:
1250it [44:15,  1.40s/it]
ChatCompletion(id='chatcmpl-9MymSshJGDBOVImyfMtgrS3aLTgRH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin information", "locate pin", "pin update"]', role='assistant', function_call=None, tool_calls=None))], created=1715263884, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["pin information", "locate pin", "pin update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where in the app can I find my PIN?"

Keyphrases:
1251it [44:17,  1.49s/it]
ChatCompletion(id='chatcmpl-9MymTxAKIYE3d3CCCAmD6hSpq0rEV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["find PIN", "PIN location", "app navigation"]', role='assistant', function_call=None, tool_calls=None))], created=1715263885, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["find PIN", "PIN location", "app navigation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I just got my new card but am not sure how to check its PIN."

Keyphrases:
1252it [44:19,  1.83s/it]
ChatCompletion(id='chatcmpl-9MymVR758HJfEtcdGcIhxU5eOPlW8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN retrieval", "activate new card", "check PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715263887, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["PIN retrieval", "activate new card", "check PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "do i need a pin"

Keyphrases:
1253it [44:21,  1.70s/it]
ChatCompletion(id='chatcmpl-9MymYvAOvWzH1yTAHCNKmGmrUlR6v', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin requirement", "card pin necessity", "ATM pin usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715263890, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["pin requirement", "card pin necessity", "ATM pin usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I need a PIN for my card, where is it located?"

Keyphrases:
1254it [44:22,  1.67s/it]
ChatCompletion(id='chatcmpl-9MymZkRvmTlNcoRlwLdv3kQNASm6H', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN retrieval", "card PIN location", "obtain PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715263891, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["PIN retrieval", "card PIN location", "obtain PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what is my card PIN"

Keyphrases:
1255it [44:24,  1.66s/it]
ChatCompletion(id='chatcmpl-9MymbMLpRWjvsnqgVFydSyzNQVrWE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card PIN", "retrieve PIN", "PIN information"]', role='assistant', function_call=None, tool_calls=None))], created=1715263893, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["card PIN", "retrieve PIN", "PIN information"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "And what about the Card's PIN?"

Keyphrases:
1256it [44:26,  1.62s/it]
ChatCompletion(id='chatcmpl-9Mymc8vaYfcqlPgV7S0WIsAYtF7I5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card PIN", "PIN setup", "PIN information"]', role='assistant', function_call=None, tool_calls=None))], created=1715263894, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["card PIN", "PIN setup", "PIN information"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "About this card PIN?"

Keyphrases:
1257it [44:27,  1.68s/it]
ChatCompletion(id='chatcmpl-9MymeLU0hNPoHZvztbEfOdIDFL15p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN inquiry", "card PIN information", "PIN assistance"]', role='assistant', function_call=None, tool_calls=None))], created=1715263896, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["PIN inquiry", "card PIN information", "PIN assistance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I received my card but not my PIN."

Keyphrases:
1258it [44:29,  1.53s/it]
ChatCompletion(id='chatcmpl-9MymgLNDdRryFHZmoM9At2Gms5r0M', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN not received", "card received without PIN", "missing PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715263898, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["PIN not received", "card received without PIN", "missing PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I see my PIN?"

Keyphrases:
1259it [44:30,  1.44s/it]
ChatCompletion(id='chatcmpl-9Mymhej3vVs7fqPOWbyyPzOM4Jx0x', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN visibility", "show PIN", "PIN issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715263899, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["PIN visibility", "show PIN", "PIN issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what is the process for setting up a pin"

Keyphrases:
1260it [44:31,  1.39s/it]
ChatCompletion(id='chatcmpl-9MymiL4fuPMbRDDdbafpl7zxQbKq7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["set up pin", "PIN configuration", "create PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715263900, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["set up pin", "PIN configuration", "create PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Does my PIN come with my card?"

Keyphrases:
1261it [44:32,  1.32s/it]
ChatCompletion(id='chatcmpl-9Mymj4WFmyuSVXvu6Z3plFHeUldqh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN delivery", "card and PIN", "receive PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715263901, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["PIN delivery", "card and PIN", "receive PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I find the card PIN?"

Keyphrases:
1262it [44:34,  1.30s/it]
ChatCompletion(id='chatcmpl-9MymlsGNNcdUaqeoUZRNL6craRuFz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card PIN location", "retrieve PIN", "PIN query"]', role='assistant', function_call=None, tool_calls=None))], created=1715263903, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card PIN location", "retrieve PIN", "PIN query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why isn't my PIN available yet?"

Keyphrases:
1263it [44:35,  1.27s/it]
ChatCompletion(id='chatcmpl-9MymmoCAHdTj3I48KEcbMnlqWZpla', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN setup", "PIN issue", "delay in PIN availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715263904, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["PIN setup", "PIN issue", "delay in PIN availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is my PIN located on my account somewhere?"

Keyphrases:
1264it [44:36,  1.34s/it]
ChatCompletion(id='chatcmpl-9Mymn3siVDyJBuFyMHiEwaDhLVoQd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN location", "find PIN", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715263905, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["PIN location", "find PIN", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please help in finding my card PIN, thank you!"

Keyphrases:
1265it [44:38,  1.47s/it]
ChatCompletion(id='chatcmpl-9MympNs9FOEcYk5RUGWaQFFPWICfe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN retrieval", "lost PIN", "find card PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715263907, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["PIN retrieval", "lost PIN", "find card PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is my PIN number located?"

Keyphrases:
1266it [44:39,  1.43s/it]
ChatCompletion(id='chatcmpl-9MymqbKGGEpRQDK6a02NhlZitK5C1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN location", "retrieve PIN", "PIN number whereabouts"]', role='assistant', function_call=None, tool_calls=None))], created=1715263908, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["PIN location", "retrieve PIN", "PIN number whereabouts"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I still don't have my pin."

Keyphrases:
1267it [44:41,  1.45s/it]
ChatCompletion(id='chatcmpl-9Myms1AuptackhACK2mNH98qJhlyt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin delivery", "missing pin", "pin not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715263910, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["pin delivery", "missing pin", "pin not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "So what about the card PIN?"

Keyphrases:
1268it [44:42,  1.39s/it]
ChatCompletion(id='chatcmpl-9MymtU8ZR2JYI2v3Dmr0tKFxlfmb9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card PIN", "PIN retrieval", "PIN information"]', role='assistant', function_call=None, tool_calls=None))], created=1715263911, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["card PIN", "PIN retrieval", "PIN information"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I cannot locate the card PIN."

Keyphrases:
1269it [44:43,  1.35s/it]
ChatCompletion(id='chatcmpl-9Mymusncsp6k4TjfwEMWrvtuiLS9R', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card PIN", "missing PIN", "locate PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715263912, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["card PIN", "missing PIN", "locate PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need my PIN"

Keyphrases:
1270it [44:45,  1.58s/it]
ChatCompletion(id='chatcmpl-9MymwZYIy5m2Gntyy0z6VwGyxKDjh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN retrieval", "forgot PIN", "PIN reset"]', role='assistant', function_call=None, tool_calls=None))], created=1715263914, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["PIN retrieval", "forgot PIN", "PIN reset"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I find my PIN?"

Keyphrases:
1271it [44:47,  1.44s/it]
ChatCompletion(id='chatcmpl-9Mymyc0EQSffN2U1WMZr96SRst9s5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN location", "find PIN", "retrieve PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715263916, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["PIN location", "find PIN", "retrieve PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When do I receive my PIN"

Keyphrases:
1272it [44:48,  1.41s/it]
ChatCompletion(id='chatcmpl-9MymzVAeFbucMksAZk8OYMBSh8PrY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN delivery", "receive PIN", "PIN issuance time"]', role='assistant', function_call=None, tool_calls=None))], created=1715263917, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["PIN delivery", "receive PIN", "PIN issuance time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help me find my card pin!"

Keyphrases:
1273it [44:49,  1.38s/it]
ChatCompletion(id='chatcmpl-9Myn03lf9kmsmDwNPvV0oYWK00ktG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin retrieval", "find card pin", "reset pin"]', role='assistant', function_call=None, tool_calls=None))], created=1715263918, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["pin retrieval", "find card pin", "reset pin"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is PIN delivered separately?"

Keyphrases:
1274it [44:51,  1.57s/it]
ChatCompletion(id='chatcmpl-9Myn2AQFBxVnzAVPn0Vev8UA0kNPz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN delivery", "separate delivery", "delivery method"]', role='assistant', function_call=None, tool_calls=None))], created=1715263920, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["PIN delivery", "separate delivery", "delivery method"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can not find my card pin."

Keyphrases:
1275it [44:54,  1.81s/it]
ChatCompletion(id='chatcmpl-9Myn4gClkdd7lr0URlPqcfRVxCynM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card pin", "pin retrieval", "lost pin"]', role='assistant', function_call=None, tool_calls=None))], created=1715263922, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["card pin", "pin retrieval", "lost pin"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I need to do for a PIN?"

Keyphrases:
1276it [44:55,  1.64s/it]
ChatCompletion(id='chatcmpl-9Myn6oufpXwOxZnOc3Q59yNY0wNGi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN setup", "create PIN", "PIN creation process"]', role='assistant', function_call=None, tool_calls=None))], created=1715263924, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["PIN setup", "create PIN", "PIN creation process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I find my PIN?"

Keyphrases:
1277it [44:57,  1.76s/it]
ChatCompletion(id='chatcmpl-9Myn7ci6ZPfOmKO43g0ce0UQhOahb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN retrieval", "lost PIN", "find PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715263925, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["PIN retrieval", "lost PIN", "find PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is the card PIN?"

Keyphrases:
1278it [44:58,  1.70s/it]
ChatCompletion(id='chatcmpl-9Myn9ifpcV2ZOXdg9tXX6EqE8nMUw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card PIN location", "PIN retrieval", "find PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715263927, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["card PIN location", "PIN retrieval", "find PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is my card's PIN?"

Keyphrases:
1279it [45:00,  1.57s/it]
ChatCompletion(id='chatcmpl-9MynBYqMBWpoVssrWtj5CdbImvYb9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card PIN", "retrieve PIN", "PIN information"]', role='assistant', function_call=None, tool_calls=None))], created=1715263929, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["card PIN", "retrieve PIN", "PIN information"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "where can user find pin?"

Keyphrases:
1280it [45:03,  2.03s/it]
ChatCompletion(id='chatcmpl-9MynCQBUYpGGg4wLJUfemmmU1ImRY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin location", "find pin", "ATM pin retrieval"]', role='assistant', function_call=None, tool_calls=None))], created=1715263930, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["pin location", "find pin", "ATM pin retrieval"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I like to Mastercard rather than Visa."

Keyphrases:
1281it [45:04,  1.82s/it]
ChatCompletion(id='chatcmpl-9MynFwyrSWphxzVW8lvtxHxDhnRLv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card preference", "Mastercard vs Visa", "credit card options"]', role='assistant', function_call=None, tool_calls=None))], created=1715263933, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["card preference", "Mastercard vs Visa", "credit card options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I qualify for a visa card?"

Keyphrases:
1282it [45:05,  1.65s/it]
ChatCompletion(id='chatcmpl-9MynGCACflVJIYrmZc6mIybE7yx2p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["visa card eligibility", "credit card qualification", "bank card application criteria"]', role='assistant', function_call=None, tool_calls=None))], created=1715263934, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["visa card eligibility", "credit card qualification", "bank card application criteria"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I get a visa card?"

Keyphrases:
1283it [45:07,  1.53s/it]
ChatCompletion(id='chatcmpl-9MynI4mOruIPP3iFxHV94mdDlp91D', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["visa card application", "apply for visa card", "obtain visa card"]', role='assistant', function_call=None, tool_calls=None))], created=1715263936, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["visa card application", "apply for visa card", "obtain visa card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you guys accept Visa or Mastercard?"

Keyphrases:
1284it [45:08,  1.50s/it]
ChatCompletion(id='chatcmpl-9MynJQ16VAiBmnY1JN3lVUxAJzeNn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "payment methods", "Visa", "Mastercard"]', role='assistant', function_call=None, tool_calls=None))], created=1715263937, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["card acceptance", "payment methods", "Visa", "Mastercard"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are both Visa and Mastercard accepted?"

Keyphrases:
1285it [45:09,  1.42s/it]
ChatCompletion(id='chatcmpl-9MynKKRueM8eUqCNHC3fVs27eXyGA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "Visa and Mastercard", "payment methods accepted"]', role='assistant', function_call=None, tool_calls=None))], created=1715263938, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["card acceptance", "Visa and Mastercard", "payment methods accepted"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you guys accept mastercard or visa?"

Keyphrases:
1286it [45:11,  1.49s/it]
ChatCompletion(id='chatcmpl-9MynMcdWWLRdzwlGyOqiSETIfy3B5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card acceptance", "payment methods", "visa acceptance", "mastercard acceptance"]', role='assistant', function_call=None, tool_calls=None))], created=1715263940, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=227, total_tokens=244))
["card acceptance", "payment methods", "visa acceptance", "mastercard acceptance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are both Visa and Mastercard offered?"

Keyphrases:
1287it [45:12,  1.44s/it]
ChatCompletion(id='chatcmpl-9MynNJx1RXh5YBNLu63cvmhPF4H4j', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card options", "Visa and Mastercard availability", "payment methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715263941, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["card options", "Visa and Mastercard availability", "payment methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you give me a visa?"

Keyphrases:
1288it [45:13,  1.33s/it]
ChatCompletion(id='chatcmpl-9MynPHnbUKxqALXy6ZCpxdtFqgAEn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["visa application", "bank visa services"]', role='assistant', function_call=None, tool_calls=None))], created=1715263943, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=9, prompt_tokens=225, total_tokens=234))
["visa application", "bank visa services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How to decide if I get a Visa or Mastercard?"

Keyphrases:
1289it [45:15,  1.37s/it]
ChatCompletion(id='chatcmpl-9MynQkWVHmpaSKvteJIfEd56fS5Cd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card choice", "Visa vs Mastercard", "credit card selection"]', role='assistant', function_call=None, tool_calls=None))], created=1715263944, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["card choice", "Visa vs Mastercard", "credit card selection"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get a mastercard?"

Keyphrases:
1290it [45:17,  1.54s/it]
ChatCompletion(id='chatcmpl-9MynRLqtf44NIavaHWs64eiGUimmZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["mastercard availability", "apply for mastercard", "card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715263945, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["mastercard availability", "apply for mastercard", "card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What steps must I follow to get a Visa credit card?"

Keyphrases:
1291it [45:20,  2.00s/it]
ChatCompletion(id='chatcmpl-9MynT0S1byA9m6jFi7z6Raf2qYEWs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["apply for credit card", "Visa credit card application", "credit card steps"]', role='assistant', function_call=None, tool_calls=None))], created=1715263947, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=18, prompt_tokens=230, total_tokens=248))
["apply for credit card", "Visa credit card application", "credit card steps"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'd rather get a Mastercard"

Keyphrases:
1292it [45:21,  1.80s/it]
ChatCompletion(id='chatcmpl-9MynWwjsCo5xjRaWmeNb92TnKcs8M', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card preference", "choose Mastercard", "switch card type"]', role='assistant', function_call=None, tool_calls=None))], created=1715263950, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["card preference", "choose Mastercard", "switch card type"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I get a choice between Visa and Mastercard?"

Keyphrases:
1293it [45:23,  1.83s/it]
ChatCompletion(id='chatcmpl-9MynYEV9P63E2rFv2S2wYf3tzN3qV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card type selection", "Visa vs Mastercard", "card options"]', role='assistant', function_call=None, tool_calls=None))], created=1715263952, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["card type selection", "Visa vs Mastercard", "card options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I have to do to get a Visa credit card?"

Keyphrases:
1294it [45:25,  1.75s/it]
ChatCompletion(id='chatcmpl-9MynZkLH91dGFIn0QYnm2GZQyAjl2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["visa credit card application", "credit card eligibility", "apply for credit card"]', role='assistant', function_call=None, tool_calls=None))], created=1715263953, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["visa credit card application", "credit card eligibility", "apply for credit card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would prefer a visa card"

Keyphrases:
1295it [45:27,  1.81s/it]
ChatCompletion(id='chatcmpl-9MynbAOcXWRCHxIpKJue9Xdg6b8B8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Visa card preference", "card type selection", "choose Visa card"]', role='assistant', function_call=None, tool_calls=None))], created=1715263955, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["Visa card preference", "card type selection", "choose Visa card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "May I choose between Visa and Mastercard?"

Keyphrases:
1296it [45:31,  2.61s/it]
ChatCompletion(id='chatcmpl-9MyndaAWelQSgMIh2QobZw3WbrCbB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card choice", "select card type", "Visa vs Mastercard"]', role='assistant', function_call=None, tool_calls=None))], created=1715263957, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["card choice", "select card type", "Visa vs Mastercard"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Am I allowed to use any card to make a payment?"

Keyphrases:
1297it [45:32,  2.23s/it]
ChatCompletion(id='chatcmpl-9MynhaeykzabBAV2NGKV1JxPpWYir', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment methods", "card usage", "allowed payment cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715263961, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["payment methods", "card usage", "allowed payment cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the available cards?"

Keyphrases:
1298it [45:34,  1.98s/it]
ChatCompletion(id='chatcmpl-9Mynjk4RVWwF3cxUqcxVmHfKnlcYU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card options", "available credit cards", "types of bank cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715263963, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["card options", "available credit cards", "types of bank cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to get Visa and Mastercard"

Keyphrases:
1299it [45:36,  1.96s/it]
ChatCompletion(id='chatcmpl-9Mynl8AhUBEWxd6y9huZ1yrTumt5B', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card types", "Visa and Mastercard", "apply for credit card"]', role='assistant', function_call=None, tool_calls=None))], created=1715263965, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=227, total_tokens=244))
["card types", "Visa and Mastercard", "apply for credit card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Am I able to choose my card?"

Keyphrases:
1300it [45:38,  2.16s/it]
ChatCompletion(id='chatcmpl-9Mynmpmxap4viesYQReUCqAavYrqY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card selection", "choose card option", "card customization"]', role='assistant', function_call=None, tool_calls=None))], created=1715263966, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card selection", "choose card option", "card customization"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "are both visa and mastercard available to me?"

Keyphrases:
1301it [45:40,  1.89s/it]
ChatCompletion(id='chatcmpl-9MynplD4sJ9RYaOQMyGSXBqlzM3nz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card options", "visa and mastercard availability", "credit card types"]', role='assistant', function_call=None, tool_calls=None))], created=1715263969, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["card options", "visa and mastercard availability", "credit card types"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you do Visa or Mastercard?"

Keyphrases:
1302it [45:43,  2.29s/it]
ChatCompletion(id='chatcmpl-9Mynq12po0FeDqjVWwVJ9matqhT9a', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card types", "Visa or Mastercard", "payment methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715263970, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["card types", "Visa or Mastercard", "payment methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I select a Mastercard instead of a Visa?"

Keyphrases:
1303it [45:44,  2.06s/it]
ChatCompletion(id='chatcmpl-9MyntM7CRA0hulAGlVi8gQAz222JT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card selection", "choose card type", "Mastercard vs Visa"]', role='assistant', function_call=None, tool_calls=None))], created=1715263973, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["card selection", "choose card type", "Mastercard vs Visa"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to apply for a visa card."

Keyphrases:
1304it [45:46,  1.86s/it]
ChatCompletion(id='chatcmpl-9MynvgkzJCi9YXMQLzWW08hNxgk4R', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["visa card application", "apply for credit card", "credit card signup"]', role='assistant', function_call=None, tool_calls=None))], created=1715263975, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["visa card application", "apply for credit card", "credit card signup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I get to choose between Visa and Mastercard?"

Keyphrases:
1305it [45:47,  1.78s/it]
ChatCompletion(id='chatcmpl-9MynwchnkBiucaJPNlWH8F1jXtbU1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card choice", "Visa vs Mastercard", "credit card options"]', role='assistant', function_call=None, tool_calls=None))], created=1715263976, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["card choice", "Visa vs Mastercard", "credit card options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "We need both a visa and a Mastercard."

Keyphrases:
1306it [45:49,  1.65s/it]
ChatCompletion(id='chatcmpl-9Myny24PmzLZnTSTtw8Rvg2e2CH7S', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple cards request", "visa and Mastercard", "card types"]', role='assistant', function_call=None, tool_calls=None))], created=1715263978, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["multiple cards request", "visa and Mastercard", "card types"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hello. Can you tell me if you use Visa or Mastercard?"

Keyphrases:
1307it [45:50,  1.63s/it]
ChatCompletion(id='chatcmpl-9Mynz0IChEO3WqQjpIiMh4VCh4jI0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card types accepted", "Visa or Mastercard", "payment methods accepted"]', role='assistant', function_call=None, tool_calls=None))], created=1715263979, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=232, total_tokens=249))
["card types accepted", "Visa or Mastercard", "payment methods accepted"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'd like more information about choosing a Visa or Mastercard."

Keyphrases:
1308it [45:52,  1.59s/it]
ChatCompletion(id='chatcmpl-9Myo1mZfMlsFWVtREV3SBSKR2HiVH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card choice", "Visa vs Mastercard", "card comparison"]', role='assistant', function_call=None, tool_calls=None))], created=1715263981, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["credit card choice", "Visa vs Mastercard", "card comparison"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you have Visa or Matercard?"

Keyphrases:
1309it [45:53,  1.49s/it]
ChatCompletion(id='chatcmpl-9Myo2ycUhVqW5jLvj5DpiZHgazuFl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card options", "Visa", "Mastercard"]', role='assistant', function_call=None, tool_calls=None))], created=1715263982, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["credit card options", "Visa", "Mastercard"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to have both a Visa and a Mastercard from you?"

Keyphrases:
1310it [45:55,  1.65s/it]
ChatCompletion(id='chatcmpl-9Myo3NRkRyHTNHnuOlBSOAbOhAOzw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple credit cards", "Visa and Mastercard", "card options"]', role='assistant', function_call=None, tool_calls=None))], created=1715263983, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["multiple credit cards", "Visa and Mastercard", "card options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I like Mastercard better."

Keyphrases:
1311it [45:58,  1.88s/it]
ChatCompletion(id='chatcmpl-9Myo5uojMCbekq4WheymVslxt3LDU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card preference", "Mastercard preference", "credit card opinion"]', role='assistant', function_call=None, tool_calls=None))], created=1715263985, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["credit card preference", "Mastercard preference", "credit card opinion"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you offer Visa or Mastercard?"

Keyphrases:
1312it [45:59,  1.84s/it]
ChatCompletion(id='chatcmpl-9Myo8rK2TkYyOZsCLfE6GvWAa8Lbg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card types", "Visa or Mastercard", "card options"]', role='assistant', function_call=None, tool_calls=None))], created=1715263988, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["card types", "Visa or Mastercard", "card options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would rather the Mastercard."

Keyphrases:
1313it [46:02,  2.02s/it]
ChatCompletion(id='chatcmpl-9MyoAHuCEbzhHS8CZbkoXP6GY3Aup', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card preference", "choose Mastercard", "card type selection"]', role='assistant', function_call=None, tool_calls=None))], created=1715263990, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["card preference", "choose Mastercard", "card type selection"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please give me both a visa and a master card."

Keyphrases:
1314it [46:03,  1.85s/it]
ChatCompletion(id='chatcmpl-9MyoCU9s6FOFzIMw4mYTQlgNj6B1H', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple cards request", "visa and mastercard request", "card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715263992, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["multiple cards request", "visa and mastercard request", "card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to receive a Visa and a MasterCard?"

Keyphrases:
1315it [46:05,  1.91s/it]
ChatCompletion(id='chatcmpl-9MyoEOChZctnZKducBjKXY9hGs5jT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple cards", "Visa and MasterCard", "card options"]', role='assistant', function_call=None, tool_calls=None))], created=1715263994, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["multiple cards", "Visa and MasterCard", "card options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What major card payments are accepted?"

Keyphrases:
1316it [46:06,  1.71s/it]
ChatCompletion(id='chatcmpl-9MyoGNFGedwLFrhznz3ilTFnJE57R', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["accepted payment methods", "card acceptance", "payment options"]', role='assistant', function_call=None, tool_calls=None))], created=1715263996, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["accepted payment methods", "card acceptance", "payment options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is Visa or Mastercard available?"

Keyphrases:
1317it [46:08,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyoHEeCVNToiNu1F5ouroA707jc9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card options", "Visa availability", "Mastercard availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715263997, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["credit card options", "Visa availability", "Mastercard availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you let me know if Visa is among the card scheme assignments?"

Keyphrases:
1318it [46:10,  1.72s/it]
ChatCompletion(id='chatcmpl-9MyoIFeUnanTHPQn1YiRsKMY17rvf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Visa card scheme", "card type inquiry", "card scheme assignment"]', role='assistant', function_call=None, tool_calls=None))], created=1715263998, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["Visa card scheme", "card type inquiry", "card scheme assignment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you use Mastercard or Visa?"

Keyphrases:
1319it [46:11,  1.54s/it]
ChatCompletion(id='chatcmpl-9MyoKBTPKM1pQmkHdC9LfGOSGFvJb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card type", "payment methods", "Mastercard or Visa"]', role='assistant', function_call=None, tool_calls=None))], created=1715264000, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["card type", "payment methods", "Mastercard or Visa"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to get a Visa here?"

Keyphrases:
1320it [46:12,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyoL9F2IK4kadqUp41b8Q3dCfrQf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Visa availability", "apply for Visa", "Visa services"]', role='assistant', function_call=None, tool_calls=None))], created=1715264001, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["Visa availability", "apply for Visa", "Visa services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I top up my account with a card?"

Keyphrases:
1321it [46:15,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyoMpMB8v62XdzZDzAIxhBVx11vG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account top-up", "card top-up", "funding account"]', role='assistant', function_call=None, tool_calls=None))], created=1715264002, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["account top-up", "card top-up", "funding account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "WHERE IS MY MONEY I WAS USING MY CARD AND IT DISAPPEARED"

Keyphrases:
1322it [46:17,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyoPvCEbJ3eCvlBbqK77cs1dfroN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing funds", "transaction issues", "disappeared money"]', role='assistant', function_call=None, tool_calls=None))], created=1715264005, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["missing funds", "transaction issues", "disappeared money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I top up by card?"

Keyphrases:
1323it [46:20,  2.15s/it]
ChatCompletion(id='chatcmpl-9MyoR7eXR4CJv4yOURWHPc7etRNwH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card top-up", "funding account", "loading money"]', role='assistant', function_call=None, tool_calls=None))], created=1715264007, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["card top-up", "funding account", "loading money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the process for using my credit card to transfer money?"

Keyphrases:
1324it [46:26,  3.52s/it]
ChatCompletion(id='chatcmpl-9MyoUGs6yCfqCVGDNj6Zzr4gwntcl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card transfer", "transfer money with credit card", "credit card usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715264010, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["credit card transfer", "transfer money with credit card", "credit card usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I top up my card using your app? I'm new to this."

Keyphrases:
1325it [46:29,  3.23s/it]
ChatCompletion(id='chatcmpl-9MyobeYWb5nE1LO3Mei8It0Mf8XGu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card top-up", "using app", "new user guide"]', role='assistant', function_call=None, tool_calls=None))], created=1715264017, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["card top-up", "using app", "new user guide"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can friends add to my account"

Keyphrases:
1326it [46:30,  2.73s/it]
ChatCompletion(id='chatcmpl-9MyodbvXz1zRRAb5VGFdTSjulzxin', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["add funds", "external deposits", "third-party contributions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264019, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["add funds", "external deposits", "third-party contributions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I top up using my car?"

Keyphrases:
1327it [46:32,  2.31s/it]
ChatCompletion(id='chatcmpl-9MyofJDORdPCliMGLK6wEDbgNAY2h', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up methods", "vehicle payment", "fund account with car"]', role='assistant', function_call=None, tool_calls=None))], created=1715264021, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["top up methods", "vehicle payment", "fund account with car"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I see my topup in my wallet anymore?"

Keyphrases:
1328it [46:33,  2.00s/it]
ChatCompletion(id='chatcmpl-9Myog52LHDsutqi96VxREbo8RS7xQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing topup", "topup not visible", "wallet balance issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264022, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["missing topup", "topup not visible", "wallet balance issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Use credit card to transfer money"

Keyphrases:
1329it [46:35,  1.83s/it]
ChatCompletion(id='chatcmpl-9MyohKucEbS8kE5zoEeYOXHj4GR1E', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card transfer", "use credit for transfer", "card to bank transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715264023, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=225, total_tokens=242))
["credit card transfer", "use credit for transfer", "card to bank transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do my friends top up my account"

Keyphrases:
1330it [46:37,  2.04s/it]
ChatCompletion(id='chatcmpl-9MyojvaH6qZcBcGxHDGlOKqvluFBK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account top-up by others", "external account funding", "friend deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715264025, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["account top-up by others", "external account funding", "friend deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I followed the instructions to transfer money using my card, but then the money disappeared and I don't know what happened."

Keyphrases:
1331it [46:39,  1.97s/it]
ChatCompletion(id='chatcmpl-9MyomLYogF5R9Nm2iGRAQW7G8M1kQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing funds", "failed transfer", "money transfer issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264028, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=242, total_tokens=255))
["missing funds", "failed transfer", "money transfer issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where's the money that got charged to my card? It's not showing up in my account balance"

Keyphrases:
1332it [46:41,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyonnNhQe1uJUWT66RnP2iWgDss0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transaction", "unaccounted charges", "transaction not showing"]', role='assistant', function_call=None, tool_calls=None))], created=1715264029, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=239, total_tokens=254))
["missing transaction", "unaccounted charges", "transaction not showing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how can i top up?"

Keyphrases:
1333it [46:42,  1.73s/it]
ChatCompletion(id='chatcmpl-9MyopqAawXISlqHAcFd6d53VCNn1a', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up account", "account recharge", "funding account"]', role='assistant', function_call=None, tool_calls=None))], created=1715264031, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["top up account", "account recharge", "funding account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am missing some funds from my account - I tried to transfer them using my credit card number, and it disappeared."

Keyphrases:
1334it [46:44,  1.72s/it]
ChatCompletion(id='chatcmpl-9Myoqo9AdzHNYcliJgBGR1PQUuZ7C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing funds", "transfer issue", "credit card transfer problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264032, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=242, total_tokens=256))
["missing funds", "transfer issue", "credit card transfer problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have friends that would like to top-up my account is that possible?"

Keyphrases:
1335it [46:45,  1.64s/it]
ChatCompletion(id='chatcmpl-9MyoslB0HMXDOefAiETq4TTquT1oH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account top-up", "third-party top-up", "external funding"]', role='assistant', function_call=None, tool_calls=None))], created=1715264034, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["account top-up", "third-party top-up", "external funding"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I transfer money using a credit card?"

Keyphrases:
1336it [46:46,  1.52s/it]
ChatCompletion(id='chatcmpl-9MyotFmF4EiQQ8QY38Z946NdF5pLU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card transfer", "money transfer", "online bank transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715264035, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["credit card transfer", "money transfer", "online bank transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I give my friends access to my account so they can top it up for me?"

Keyphrases:
1337it [46:48,  1.41s/it]
ChatCompletion(id='chatcmpl-9MyovufaZwEJd9E9D27QQOl3Ts1OY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account access", "delegate access", "third-party top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715264037, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=236, total_tokens=250))
["account access", "delegate access", "third-party top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I did a top-up, but I'm not seeing it in my wallet yet."

Keyphrases:
1338it [46:51,  2.07s/it]
ChatCompletion(id='chatcmpl-9Myow43Uvp0lBC262wTcu89XcmpRf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up missing", "wallet balance issue", "transaction not reflected"]', role='assistant', function_call=None, tool_calls=None))], created=1715264038, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=235, total_tokens=250))
["top-up missing", "wallet balance issue", "transaction not reflected"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "i know i entered the right info, but my top up isn't in my balance"

Keyphrases:
1339it [46:53,  1.95s/it]
ChatCompletion(id='chatcmpl-9MyozoOosvQ1V6qQVj5J2dudjpg96', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "balance discrepancy", "funds not credited"]', role='assistant', function_call=None, tool_calls=None))], created=1715264041, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["top up issue", "balance discrepancy", "funds not credited"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will my friend be able to top off my account?"

Keyphrases:
1340it [46:54,  1.75s/it]
ChatCompletion(id='chatcmpl-9Myp1dTfiQt9HGPB2GkLAq4Jxbocd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account top off", "third-party deposit", "external deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715264043, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["account top off", "third-party deposit", "external deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a way to transfer funds directly from my card?"

Keyphrases:
1341it [46:57,  2.03s/it]
ChatCompletion(id='chatcmpl-9Myp2jjjSOJWB4ww5tnIj0xGh9IEb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer", "direct card transfer", "card to account transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715264044, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["fund transfer", "direct card transfer", "card to account transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why isn't my top up showing on my wallet?"

Keyphrases:
1342it [47:00,  2.52s/it]
ChatCompletion(id='chatcmpl-9Myp57p8PSzQA34NlnhV7O8F58G1C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "wallet balance not updated", "missing funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715264047, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["top up issue", "wallet balance not updated", "missing funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to top up using my card, but now the money just disappeared!"

Keyphrases:
1343it [47:02,  2.18s/it]
ChatCompletion(id='chatcmpl-9Myp995lOVk57WCgbFlMXZi2Rrby9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "missing funds", "card top up problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264051, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["top up issue", "missing funds", "card top up problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help me transfer money to my credit card."

Keyphrases:
1344it [47:05,  2.44s/it]
ChatCompletion(id='chatcmpl-9MypAxznTIgSMKU6OktMHhN2cyyKF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "credit card funding", "transfer to credit card"]', role='assistant', function_call=None, tool_calls=None))], created=1715264052, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["money transfer", "credit card funding", "transfer to credit card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to use my card to top up but all of the money has disappeared."

Keyphrases:
1345it [47:07,  2.21s/it]
ChatCompletion(id='chatcmpl-9MypDi5ULoL5MioZidVdVvZbejTiR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card transaction issue", "top up error", "missing funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715264055, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["card transaction issue", "top up error", "missing funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to use my credit card to transfer money?"

Keyphrases:
1346it [47:09,  2.37s/it]
ChatCompletion(id='chatcmpl-9MypF4VMPjJjtzlwapXh3TgW4qhDP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card transfer", "use credit card", "money transfer with credit card"]', role='assistant', function_call=None, tool_calls=None))], created=1715264057, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["credit card transfer", "use credit card", "money transfer with credit card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can someone add money to my account?"

Keyphrases:
1347it [47:11,  2.07s/it]
ChatCompletion(id='chatcmpl-9MypIgxteAQxEbUkDpNGP83Uk00pR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["add money", "external deposit", "receive funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715264060, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["add money", "external deposit", "receive funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Cannot access my top up."

Keyphrases:
1348it [47:12,  1.84s/it]
ChatCompletion(id='chatcmpl-9MypJPIR0gNhSkVzb9MYJ5LYTuKkM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "access top up", "top up failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715264061, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["top up issue", "access top up", "top up failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are my friends able to add funds to my account?"

Keyphrases:
1349it [47:13,  1.69s/it]
ChatCompletion(id='chatcmpl-9MypKvYaaWThxCohdMPENEmjI2anj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer", "external deposit", "friends add money"]', role='assistant', function_call=None, tool_calls=None))], created=1715264062, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["fund transfer", "external deposit", "friends add money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I transfer money to my credit card?"

Keyphrases:
1350it [47:15,  1.79s/it]
ChatCompletion(id='chatcmpl-9MypMGGrydVvtfunUn3nkmcbUX1MX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "credit card transfer", "bank transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715264064, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["money transfer", "credit card transfer", "bank transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Who else can top up my account"

Keyphrases:
1351it [47:17,  1.65s/it]
ChatCompletion(id='chatcmpl-9MypOcrfOZGTPVvVwxKFcC4XxnT3W', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account top-up", "third-party top-up", "external top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715264066, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["account top-up", "third-party top-up", "external top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my money gone right when I attempted to top up"

Keyphrases:
1352it [47:20,  2.14s/it]
ChatCompletion(id='chatcmpl-9MypPR16sB3krO5rY6ViKrCrHqm4L', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "missing funds", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715264067, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["top up issue", "missing funds", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do i transfer money using my credit card?"

Keyphrases:
1353it [47:22,  2.11s/it]
ChatCompletion(id='chatcmpl-9MypSNltdZa9Wigwh048pVGsxzJlJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card transfer", "money transfer", "transfer using credit card"]', role='assistant', function_call=None, tool_calls=None))], created=1715264070, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["credit card transfer", "money transfer", "transfer using credit card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My friends want to top up my account"

Keyphrases:
1354it [47:25,  2.46s/it]
ChatCompletion(id='chatcmpl-9MypUSZC4cxgSTJ5rPDq3mt7Zldqy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account top-up", "top-up by others", "external top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715264072, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["account top-up", "top-up by others", "external top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Who can top up my accounts?"

Keyphrases:
1355it [47:27,  2.28s/it]
ChatCompletion(id='chatcmpl-9MypYBAn2YkHdigA52cpJrKxeh4yI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account top-up", "top-up authorization", "permissible top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715264076, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["account top-up", "top-up authorization", "permissible top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "show me how to top up with my card"

Keyphrases:
1356it [47:29,  2.06s/it]
ChatCompletion(id='chatcmpl-9MypZDeBjyJzzIYcZHcfEJqK1xMh2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card top-up", "how to top-up", "top-up instructions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264077, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["card top-up", "how to top-up", "top-up instructions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I topped up my card but the money disappeared."

Keyphrases:
1357it [47:30,  1.84s/it]
ChatCompletion(id='chatcmpl-9MypbpluulbXT0bqlonZwkjReLqep', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "missing funds", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715264079, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["top up issue", "missing funds", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why don't I see my top up in my wallet?"

Keyphrases:
1358it [47:32,  1.87s/it]
ChatCompletion(id='chatcmpl-9MypcA6Y8ZqPZ89ImOldqfvVQnlvZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up missing", "wallet balance issue", "missing funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715264080, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["top up missing", "wallet balance issue", "missing funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I see the top-up amount I just added to my account?"

Keyphrases:
1359it [47:34,  1.92s/it]
ChatCompletion(id='chatcmpl-9Mypee7bRHvnZS4yXhi3eHBqCDgZz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "missing funds", "account balance update"]', role='assistant', function_call=None, tool_calls=None))], created=1715264082, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["top-up issue", "missing funds", "account balance update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are my friends able to top up my account?"

Keyphrases:
1360it [47:39,  2.78s/it]
ChatCompletion(id='chatcmpl-9MypgWviEVTshiQLbCZDI9JnMCfzP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account top-up by others", "external top-up", "account funding options"]', role='assistant', function_call=None, tool_calls=None))], created=1715264084, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["account top-up by others", "external top-up", "account funding options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can i get multiple disposble cards."

Keyphrases:
1361it [47:41,  2.50s/it]
ChatCompletion(id='chatcmpl-9MypljdZad5o89g5MrB9LT8nrRiVu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple cards", "disposable card request", "obtain multiple disposable cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715264089, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=227, total_tokens=244))
["multiple cards", "disposable card request", "obtain multiple disposable cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I make many disposable cards per day?"

Keyphrases:
1362it [47:42,  2.22s/it]
ChatCompletion(id='chatcmpl-9MypnH5rfopph7nCmL9TLWXTuJXjk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple disposable cards", "daily card limit", "disposable card creation"]', role='assistant', function_call=None, tool_calls=None))], created=1715264091, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["multiple disposable cards", "daily card limit", "disposable card creation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to use my disposable card multiple times a day, is there a cutoff limit?"

Keyphrases:
1363it [47:44,  2.21s/it]
ChatCompletion(id='chatcmpl-9MypoAl62MyVAFQLfoYv2WnSMqHcZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card limits", "multiple transactions", "daily cutoff limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715264092, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["disposable card limits", "multiple transactions", "daily cutoff limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I make more than one disposable card in a day?"

Keyphrases:
1364it [47:46,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyprmE9qoAcNICk337phyC4yrJwn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple disposable cards", "daily card limit", "create multiple cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715264095, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["multiple disposable cards", "daily card limit", "create multiple cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I have more than one disposable card?"

Keyphrases:
1365it [47:47,  1.90s/it]
ChatCompletion(id='chatcmpl-9MypsJuX9L6LkdrhCF3rn03OuZAea', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple disposable cards", "extra card request", "additional disposable card"]', role='assistant', function_call=None, tool_calls=None))], created=1715264096, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["multiple disposable cards", "extra card request", "additional disposable card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what is the disposable cards limit?"

Keyphrases:
1366it [47:50,  2.01s/it]
ChatCompletion(id='chatcmpl-9MypuwVUu0myeGzz2Feiw0NEW71zo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card limit", "card usage limit", "spending limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715264098, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["disposable card limit", "card usage limit", "spending limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What's the most disposable cards I can have?"

Keyphrases:
1367it [47:54,  2.79s/it]
ChatCompletion(id='chatcmpl-9Mypws9crb3wDwDOa0FqSa9yy2WIo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["maximum disposable cards", "disposable card limit", "card quantity limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715264100, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["maximum disposable cards", "disposable card limit", "card quantity limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do these virtual cards have any caps on using them?"

Keyphrases:
1368it [47:56,  2.33s/it]
ChatCompletion(id='chatcmpl-9Myq1oPDci8hlNFi5KzKxVd7ShNKt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card limits", "card usage caps", "usage restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264105, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["virtual card limits", "card usage caps", "usage restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many disposable cards can I have?"

Keyphrases:
1369it [47:57,  2.12s/it]
ChatCompletion(id='chatcmpl-9Myq2t9R6HRwgJZSpK4A50WyZHvFL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable cards limit", "number of disposable cards", "card limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715264106, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["disposable cards limit", "number of disposable cards", "card limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the amount of disposable cards I can have each day?"

Keyphrases:
1370it [47:59,  1.87s/it]
ChatCompletion(id='chatcmpl-9Myq3Oc6qhy0Thztyd1kLCJmB35OJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable cards limit", "daily card limit", "number of disposable cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715264107, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["disposable cards limit", "daily card limit", "number of disposable cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many disposable cards per day am I allowed to have?"

Keyphrases:
1371it [48:02,  2.24s/it]
ChatCompletion(id='chatcmpl-9Myq5H1drK38YhgFaJItOFEXWqvW2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable cards limit", "daily card limit", "card issuance rules"]', role='assistant', function_call=None, tool_calls=None))], created=1715264109, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["disposable cards limit", "daily card limit", "card issuance rules"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many card payments can I use on a disposable card?"

Keyphrases:
1372it [48:04,  2.21s/it]
ChatCompletion(id='chatcmpl-9Myq88ZRifFA89ZF2oYweY2xESBXl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card limits", "card payment limits", "usage limits on disposable card"]', role='assistant', function_call=None, tool_calls=None))], created=1715264112, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=230, total_tokens=248))
["disposable card limits", "card payment limits", "usage limits on disposable card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What if I need multiple disposable cards?"

Keyphrases:
1373it [48:06,  2.19s/it]
ChatCompletion(id='chatcmpl-9MyqAz4TOJGXLxlkkfnnlPyytXNJS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple cards", "disposable card request", "additional cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715264114, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["multiple cards", "disposable card request", "additional cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I have more than one disposable card, can I make five payments on each of them?"

Keyphrases:
1374it [48:11,  3.00s/it]
ChatCompletion(id='chatcmpl-9MyqCXDJbcnwP6iZKRUcFJ5TYW5GX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple disposable cards", "payment limits per card", "usage of disposable cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715264116, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=17, prompt_tokens=237, total_tokens=254))
["multiple disposable cards", "payment limits per card", "usage of disposable cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are you able to explain the restrictions of the disposable cards?"

Keyphrases:
1375it [48:12,  2.50s/it]
ChatCompletion(id='chatcmpl-9MyqHWvgmONShuGMmqy7uFMXZRfma', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card limits", "card restrictions", "card usage rules"]', role='assistant', function_call=None, tool_calls=None))], created=1715264121, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["disposable card limits", "card restrictions", "card usage rules"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the maximum number of transactions I can make with one card?"

Keyphrases:
1376it [48:14,  2.19s/it]
ChatCompletion(id='chatcmpl-9MyqIGq481PUXaZEaIv431CJIErPF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction limits", "card usage limits", "maximum transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264122, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["transaction limits", "card usage limits", "maximum transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the limit to number of transactions I can do with a disposable card?"

Keyphrases:
1377it [48:15,  1.99s/it]
ChatCompletion(id='chatcmpl-9MyqKJzzU1mE6RAtptITlWcPduFQV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction limit", "disposable card limits", "card usage restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264124, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["transaction limit", "disposable card limits", "card usage restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many disposable cards is the limit?"

Keyphrases:
1378it [48:17,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyqLuEfAiNNl3y3HnTlPcPY8FyUz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card limit", "card quantity limit", "maximum disposable cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715264125, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["disposable card limit", "card quantity limit", "maximum disposable cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Tell me how many transactions I can do with a disposable card."

Keyphrases:
1379it [48:18,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyqNG7RCEBpI1NLgQITlv8ZREYTg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card limits", "transaction limits", "card usage rules"]', role='assistant', function_call=None, tool_calls=None))], created=1715264127, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["disposable card limits", "transaction limits", "card usage rules"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have to have several disposable cards per day."

Keyphrases:
1380it [48:20,  1.73s/it]
ChatCompletion(id='chatcmpl-9MyqPQ0uaFaJViX5of0goHMiuXBzM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable cards", "multiple cards", "daily card limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715264129, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["disposable cards", "multiple cards", "daily card limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to know any restrictions for the disposable cards."

Keyphrases:
1381it [48:22,  1.87s/it]
ChatCompletion(id='chatcmpl-9MyqQ9tUPR9jJYqHf8ZKFGAEDZpem', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card restrictions", "card usage limits", "card conditions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264130, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["disposable card restrictions", "card usage limits", "card conditions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I create many temporary cards daily?"

Keyphrases:
1382it [48:23,  1.68s/it]
ChatCompletion(id='chatcmpl-9MyqSGsS6rEF3SZeXBKWy9G8GBoz0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["temporary cards", "create multiple cards", "daily card creation"]', role='assistant', function_call=None, tool_calls=None))], created=1715264132, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["temporary cards", "create multiple cards", "daily card creation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to make several disposable cards in a day?"

Keyphrases:
1383it [48:25,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyqUzlWU9gXt5FQ50E7CsIMCb6xn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple disposable cards", "daily card limit", "card issuance limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715264134, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["multiple disposable cards", "daily card limit", "card issuance limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many disposable cards can I make in a single day?"

Keyphrases:
1384it [48:26,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyqV9VFpaEeEq8C4Wuhdscv4FafG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable cards limit", "daily card limit", "card creation limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715264135, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["disposable cards limit", "daily card limit", "card creation limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a limit to how many transactions I can make on one disposable card?"

Keyphrases:
1385it [48:29,  2.01s/it]
ChatCompletion(id='chatcmpl-9MyqXXzJQLwokGiwrEtuI7FD64mAr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction limit", "disposable card limits", "card usage restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264137, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["transaction limit", "disposable card limits", "card usage restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there any limits to how many disposable cards I can use?"

Keyphrases:
1386it [48:34,  2.79s/it]
ChatCompletion(id='chatcmpl-9Myqaej9hIgDdFJukGgfk7SZV0eGp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card limits", "card usage limits", "number of cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715264140, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["disposable card limits", "card usage limits", "number of cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you explain the virtual cards limit?"

Keyphrases:
1387it [48:36,  2.63s/it]
ChatCompletion(id='chatcmpl-9MyqelJYCaBvp4jKCK7bFlil6zwNB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card limit", "card usage limit", "virtual card restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264144, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["virtual card limit", "card usage limit", "virtual card restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many disposable virtual cards can I have?"

Keyphrases:
1388it [48:38,  2.42s/it]
ChatCompletion(id='chatcmpl-9MyqhaBJJmTTynlMJX9xylpmrNXTZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card limits", "number of virtual cards", "disposable card policy"]', role='assistant', function_call=None, tool_calls=None))], created=1715264147, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=227, total_tokens=244))
["virtual card limits", "number of virtual cards", "disposable card policy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to create several disposable cards per day."

Keyphrases:
1389it [48:41,  2.49s/it]
ChatCompletion(id='chatcmpl-9MyqjOx7WUtAWLgmSLpZJdIgjLoPm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable cards", "create multiple cards", "daily card creation"]', role='assistant', function_call=None, tool_calls=None))], created=1715264149, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["disposable cards", "create multiple cards", "daily card creation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there any hindrances to using a disposable virtual card?"

Keyphrases:
1390it [48:42,  2.15s/it]
ChatCompletion(id='chatcmpl-9MyqlwT5I5jIDuJ0G8FnadqzKt2tu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card usage", "limitations of disposable card", "virtual card restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264151, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["virtual card usage", "limitations of disposable card", "virtual card restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many disposable cards can I own?"

Keyphrases:
1391it [48:44,  1.89s/it]
ChatCompletion(id='chatcmpl-9Myqnn3YAmKv54EWCHM4bmqjMIQ03', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable cards limit", "number of disposable cards", "card ownership rules"]', role='assistant', function_call=None, tool_calls=None))], created=1715264153, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["disposable cards limit", "number of disposable cards", "card ownership rules"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many virtual cards do I get?"

Keyphrases:
1392it [48:45,  1.80s/it]
ChatCompletion(id='chatcmpl-9MyqoSVUZRlVNelkZDdf1wjFWAa2k', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card limit", "number of virtual cards", "virtual card allocation"]', role='assistant', function_call=None, tool_calls=None))], created=1715264154, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["virtual card limit", "number of virtual cards", "virtual card allocation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the limit to disposable cards you can have?"

Keyphrases:
1393it [48:47,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyqpVPBnIe32qSJvOoc8whOMNwYG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card limit", "disposable card limit", "card restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264155, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["card limit", "disposable card limit", "card restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many times can I use a disposable card?"

Keyphrases:
1394it [48:48,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyqrZhWfAnGVTEEIDyfmlzDcc5ay', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card limits", "card usage frequency", "card usage rules"]', role='assistant', function_call=None, tool_calls=None))], created=1715264157, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["disposable card limits", "card usage frequency", "card usage rules"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What can I use a virtual disposable card for?"

Keyphrases:
1395it [48:50,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyqtLRWKGgpW3GLNpzkLqjEjN021', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card usage", "disposable card benefits", "virtual card purposes"]', role='assistant', function_call=None, tool_calls=None))], created=1715264159, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["virtual card usage", "disposable card benefits", "virtual card purposes"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you know what the restriction of the disposable cards are?"

Keyphrases:
1396it [48:52,  1.65s/it]
ChatCompletion(id='chatcmpl-9MyquBXqx3ei09roI6KFCLv0xEjtH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card restrictions", "disposable card limits", "usage limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715264160, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["card restrictions", "disposable card limits", "usage limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the limits for disposable virtual cards?"

Keyphrases:
1397it [48:54,  1.74s/it]
ChatCompletion(id='chatcmpl-9MyqwIuFRzifyL2gu7qY6aqkHYsFq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card limits", "disposable card restrictions", "card spending limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715264162, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["virtual card limits", "disposable card restrictions", "card spending limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the limits to using disposable virtual cards?"

Keyphrases:
1398it [48:56,  1.90s/it]
ChatCompletion(id='chatcmpl-9MyqyN4ULHnRAkFnXBCAAMLjBUF9c', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card limits", "disposable card usage", "virtual card restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264164, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["virtual card limits", "disposable card usage", "virtual card restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many transactions can I do with one disposable card?"

Keyphrases:
1399it [48:57,  1.73s/it]
ChatCompletion(id='chatcmpl-9Myr0VzbRoJLSyBSKHWFNyPtFnsA3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card limits", "transaction limits", "card usage restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264166, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["disposable card limits", "transaction limits", "card usage restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many times can I use the disposable virtual card I have?"

Keyphrases:
1400it [48:58,  1.62s/it]
ChatCompletion(id='chatcmpl-9Myr1JTMiExgOoDHUwiFDYAE2haeJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card usage", "disposable card limits", "virtual card frequency"]', role='assistant', function_call=None, tool_calls=None))], created=1715264167, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["virtual card usage", "disposable card limits", "virtual card frequency"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think someone is using my card to make transactions I don't remember."

Keyphrases:
1401it [49:00,  1.58s/it]
ChatCompletion(id='chatcmpl-9Myr36ds5sG6uATozaVw2UZe9Aky0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transactions", "fraudulent charges", "card misuse"]', role='assistant', function_call=None, tool_calls=None))], created=1715264169, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["unauthorized transactions", "fraudulent charges", "card misuse"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "someone is using my account"

Keyphrases:
1402it [49:01,  1.51s/it]
ChatCompletion(id='chatcmpl-9Myr4c832X93cbK2DYqZjxr80GRK3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized access", "account security", "fraudulent activity"]', role='assistant', function_call=None, tool_calls=None))], created=1715264170, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["unauthorized access", "account security", "fraudulent activity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone I don't know has used my card without permission."

Keyphrases:
1403it [49:03,  1.55s/it]
ChatCompletion(id='chatcmpl-9Myr6544r1y5R1OZFtxNhGhAroSoj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraudulent charge", "card misuse"]', role='assistant', function_call=None, tool_calls=None))], created=1715264172, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["unauthorized transaction", "fraudulent charge", "card misuse"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card was used without my permission."

Keyphrases:
1404it [49:04,  1.55s/it]
ChatCompletion(id='chatcmpl-9Myr7LS16Qnzrar8JMgsAs4i0tPIU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized card use", "fraudulent transaction", "card security"]', role='assistant', function_call=None, tool_calls=None))], created=1715264173, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["unauthorized card use", "fraudulent transaction", "card security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I freeze my card right now?"

Keyphrases:
1405it [49:06,  1.42s/it]
ChatCompletion(id='chatcmpl-9Myr9gKl76INYyXydagtCS5OZxPaU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["freeze card", "card security", "block card"]', role='assistant', function_call=None, tool_calls=None))], created=1715264175, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["freeze card", "card security", "block card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Freeze my account it's been hacked."

Keyphrases:
1406it [49:07,  1.36s/it]
ChatCompletion(id='chatcmpl-9MyrAsxc6g09KdugdJ6pXemTWsMNB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account security", "freeze account", "account hacked"]', role='assistant', function_call=None, tool_calls=None))], created=1715264176, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["account security", "freeze account", "account hacked"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There are transactions I didn't make, someone else must have used my card."

Keyphrases:
1407it [49:09,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyrBU7Pv5dUJV5Gymic9WkaNlD9l', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transactions", "fraudulent charges", "card misuse"]', role='assistant', function_call=None, tool_calls=None))], created=1715264177, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["unauthorized transactions", "fraudulent charges", "card misuse"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you freeze my card because someone used it while I was out of town. I did not make these purchases."

Keyphrases:
1408it [49:10,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyrDEAiJJUgL6Z7TiLI4qDR4E9a4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["freeze card", "unauthorized transaction", "card security"]', role='assistant', function_call=None, tool_calls=None))], created=1715264179, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=241, total_tokens=254))
["freeze card", "unauthorized transaction", "card security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone is using my account to do online shopping! Please freeze it asap"

Keyphrases:
1409it [49:13,  1.88s/it]
ChatCompletion(id='chatcmpl-9MyrEwVWyAowYDPrgbeG0Ex0qIhzy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account security", "freeze account", "unauthorized access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264180, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["account security", "freeze account", "unauthorized access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone else may be using my card.  There are transactions I don't recognize."

Keyphrases:
1410it [49:16,  2.34s/it]
ChatCompletion(id='chatcmpl-9MyrHT10RwirMUABKXLtwBoyuUsbH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transactions", "fraudulent charges", "card security"]', role='assistant', function_call=None, tool_calls=None))], created=1715264183, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=235, total_tokens=250))
["unauthorized transactions", "fraudulent charges", "card security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do to stop unauthorized transactions on my card? I was never in the place from which the transactions on my bill were made and I never made them. Please help!"

Keyphrases:
1411it [49:18,  2.22s/it]
ChatCompletion(id='chatcmpl-9MyrLAgfmqo8P7blf8liyL1eq6Ueu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fraudulent transactions", "unauthorized transactions", "block card", "report fraud"]', role='assistant', function_call=None, tool_calls=None))], created=1715264187, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=19, prompt_tokens=254, total_tokens=273))
["fraudulent transactions", "unauthorized transactions", "block card", "report fraud"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do if I think my card was improperly used?"

Keyphrases:
1412it [49:19,  1.89s/it]
ChatCompletion(id='chatcmpl-9MyrMce8PVAiSRBhxVDeZJA2PL4xe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card misuse", "fraudulent transaction", "unauthorized use"]', role='assistant', function_call=None, tool_calls=None))], created=1715264188, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["card misuse", "fraudulent transaction", "unauthorized use"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I stop fraud on my account right now?"

Keyphrases:
1413it [49:21,  1.85s/it]
ChatCompletion(id='chatcmpl-9MyrOjIWniuy3fvdBIoPYM2A3jrt0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fraud prevention", "stop fraud", "immediate fraud action", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715264190, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=19, prompt_tokens=229, total_tokens=248))
["fraud prevention", "stop fraud", "immediate fraud action", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think my identity has been stolen, can you check on unauthorized charges?"

Keyphrases:
1414it [49:26,  2.85s/it]
ChatCompletion(id='chatcmpl-9MyrPnbB0M53BtKmHSiNIgikmwWyK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity theft", "unauthorized charges", "fraudulent activity"]', role='assistant', function_call=None, tool_calls=None))], created=1715264191, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["identity theft", "unauthorized charges", "fraudulent activity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think someone else is using my card.  There are transactions I didn't make."

Keyphrases:
1415it [49:28,  2.37s/it]
ChatCompletion(id='chatcmpl-9MyrVPnPsQjJh7AdcXt37fPup74Pi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fraudulent transactions", "unauthorized card use", "card security breach"]', role='assistant', function_call=None, tool_calls=None))], created=1715264197, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=17, prompt_tokens=236, total_tokens=253))
["fraudulent transactions", "unauthorized card use", "card security breach"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't recognize some of the transactions on my card, I think someone must have gotten my card info and used it."

Keyphrases:
1416it [49:29,  2.18s/it]
ChatCompletion(id='chatcmpl-9MyrWOGsTBrTPue9bIuQGPzEE6otc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transactions", "fraudulent charges", "card security breach"]', role='assistant', function_call=None, tool_calls=None))], created=1715264198, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=243, total_tokens=259))
["unauthorized transactions", "fraudulent charges", "card security breach"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use app to freeze account and dispute fraud?"

Keyphrases:
1417it [49:32,  2.35s/it]
ChatCompletion(id='chatcmpl-9MyrY1DX9bKiwEzrdrHyLmNwLo2nS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["freeze account", "dispute fraud", "app functionality"]', role='assistant', function_call=None, tool_calls=None))], created=1715264200, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["freeze account", "dispute fraud", "app functionality"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is being used online to make a bunch of purchases! Someone else is using it fraudulently. Can you help me freeze it?"

Keyphrases:
1418it [49:51,  7.27s/it]
ChatCompletion(id='chatcmpl-9MyrajwrDU41JGsgILMDoqW6Fzqsh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fraud", "freeze card", "unauthorized transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264202, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=247, total_tokens=260))
["card fraud", "freeze card", "unauthorized transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone has my card number, freeze my account."

Keyphrases:
1419it [49:52,  5.61s/it]
ChatCompletion(id='chatcmpl-9Myrtdt7YN0knx8pnP0rnNXcB1L1f', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["freeze account", "card security", "fraudulent activity"]', role='assistant', function_call=None, tool_calls=None))], created=1715264221, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["freeze account", "card security", "fraudulent activity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I see random purchases to my account, was it hacked?"

Keyphrases:
1420it [49:54,  4.46s/it]
ChatCompletion(id='chatcmpl-9MyrvjQm5BLZiLY7N10S4j1AcjMAh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account security", "fraudulent transactions", "account hacking"]', role='assistant', function_call=None, tool_calls=None))], created=1715264223, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["account security", "fraudulent transactions", "account hacking"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It seems someone used my card! There are a few transactions from a small town in the middle of nowhere that I definitely have not made! Please prevent them from using it immediately!"

Keyphrases:
1421it [49:56,  3.67s/it]
ChatCompletion(id='chatcmpl-9MyrxMATqroSFD4Cv1iaCsVnx1DRX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fraudulent transactions", "block card", "unauthorized use"]', role='assistant', function_call=None, tool_calls=None))], created=1715264225, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=254, total_tokens=269))
["fraudulent transactions", "block card", "unauthorized use"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I freeze my card using the app?"

Keyphrases:
1422it [49:58,  3.27s/it]
ChatCompletion(id='chatcmpl-9Myrz9D7WddlbPkfPrGYg96szCQxr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["freeze card", "security features", "mobile app functionality"]', role='assistant', function_call=None, tool_calls=None))], created=1715264227, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["freeze card", "security features", "mobile app functionality"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card has been compromised"

Keyphrases:
1423it [50:00,  2.66s/it]
ChatCompletion(id='chatcmpl-9Mys1PEGhxNuvkpKRJlyeizt9BXWL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card compromised", "fraudulent transactions", "block card"]', role='assistant', function_call=None, tool_calls=None))], created=1715264229, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["card compromised", "fraudulent transactions", "block card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What should I do if I think that someone else may be using my card."

Keyphrases:
1424it [50:01,  2.36s/it]
ChatCompletion(id='chatcmpl-9Mys2VuZi1M3ZKNx0ryCShZW1I5nQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card security", "unauthorized use", "fraudulent transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264230, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["card security", "unauthorized use", "fraudulent transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The transactions showing up are strange, I think my card was used without me knowing."

Keyphrases:
1425it [50:04,  2.48s/it]
ChatCompletion(id='chatcmpl-9Mys4Cm0C9GUMWbhlS4FQNSAK7XjF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["suspicious transactions", "fraudulent activity", "unauthorized use"]', role='assistant', function_call=None, tool_calls=None))], created=1715264232, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=235, total_tokens=252))
["suspicious transactions", "fraudulent activity", "unauthorized use"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I freeze my account?"

Keyphrases:
1426it [50:05,  2.07s/it]
ChatCompletion(id='chatcmpl-9Mys6n1UiCyH8lYaene0fBrVurr9U', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["freeze account", "account security", "block account access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264234, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["freeze account", "account security", "block account access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm not certain, but someone may be using my card."

Keyphrases:
1427it [50:07,  1.91s/it]
ChatCompletion(id='chatcmpl-9Mys8nDeQUAcrKKL8sjxtFQ1PpcOY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card security", "unauthorized use", "fraudulent transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264236, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["card security", "unauthorized use", "fraudulent transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I freeze my card? I think someone is using it to make a bunch of online transactions."

Keyphrases:
1428it [50:08,  1.77s/it]
ChatCompletion(id='chatcmpl-9Mys9iI7EokpdAiKwWpiUDWyImiAI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["freeze card", "card security", "unauthorized transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264237, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=239, total_tokens=252))
["freeze card", "card security", "unauthorized transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think someone got my card details and used it because there are transactions i don't recognize. What do I do now?"

Keyphrases:
1429it [50:10,  1.76s/it]
ChatCompletion(id='chatcmpl-9MysBHSayvEw1XiFHZO45FNHiTEXC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fraudulent transactions", "unrecognized transactions", "report card misuse"]', role='assistant', function_call=None, tool_calls=None))], created=1715264239, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=243, total_tokens=259))
["fraudulent transactions", "unrecognized transactions", "report card misuse"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone else used my card!"

Keyphrases:
1430it [50:12,  1.79s/it]
ChatCompletion(id='chatcmpl-9MysCg8wHKe0GEHEPcSnEUUp1yhc2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "card misuse", "fraudulent charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715264240, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["unauthorized transaction", "card misuse", "fraudulent charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I believe someone is using my card without my agreement!"

Keyphrases:
1431it [50:14,  1.96s/it]
ChatCompletion(id='chatcmpl-9MysEI8uUlptm7xttdJMFMfcj6Ydw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized card use", "fraudulent transaction", "report stolen card"]', role='assistant', function_call=None, tool_calls=None))], created=1715264242, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["unauthorized card use", "fraudulent transaction", "report stolen card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I feel someone has my card information, can I get a new card?"

Keyphrases:
1432it [50:16,  1.98s/it]
ChatCompletion(id='chatcmpl-9MysGUQXQIW5AxC9VEU3NJwy3SKhW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card security", "replace card", "compromised card information"]', role='assistant', function_call=None, tool_calls=None))], created=1715264244, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["card security", "replace card", "compromised card information"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There are a few transaction that I don't recognize, I think someone managed to get my card details and use it."

Keyphrases:
1433it [50:18,  2.07s/it]
ChatCompletion(id='chatcmpl-9MysIvTcVz0onITFpBoBSe3eG9UP2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transactions", "fraudulent transactions", "card security breach"]', role='assistant', function_call=None, tool_calls=None))], created=1715264246, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=242, total_tokens=258))
["unrecognized transactions", "fraudulent transactions", "card security breach"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think someone has access to my card numbers that shouldn't."

Keyphrases:
1434it [50:21,  2.30s/it]
ChatCompletion(id='chatcmpl-9MysLlhV3HrnQXvLvsACQ4U006Q18', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card security", "unauthorized access", "compromised card"]', role='assistant', function_call=None, tool_calls=None))], created=1715264249, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["card security", "unauthorized access", "compromised card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think my child used my card while I wasn't home."

Keyphrases:
1435it [50:23,  2.16s/it]
ChatCompletion(id='chatcmpl-9MysOdead82YmZbP0hvTnADBSOlOI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "card misuse", "fraudulent charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715264252, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["unauthorized transaction", "card misuse", "fraudulent charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do if I think someone managed to get my card information?"

Keyphrases:
1436it [50:24,  1.88s/it]
ChatCompletion(id='chatcmpl-9MysP8o0WHOcJnFR4YHkNWvg1o5gi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card security", "compromised card", "fraudulent activity"]', role='assistant', function_call=None, tool_calls=None))], created=1715264253, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["card security", "compromised card", "fraudulent activity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think someone copied the numbers on my card and is using them."

Keyphrases:
1437it [50:26,  1.73s/it]
ChatCompletion(id='chatcmpl-9MysRfRQuSkbgknvT20Pg2D1GzJNL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card security", "fraudulent transactions", "stolen card details"]', role='assistant', function_call=None, tool_calls=None))], created=1715264255, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["card security", "fraudulent transactions", "stolen card details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What should I do if I think someone is using my card."

Keyphrases:
1438it [50:29,  2.24s/it]
ChatCompletion(id='chatcmpl-9MysSeMi2IfyubHokpxioqwxHbuyW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card security", "unauthorized card use", "fraudulent transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264256, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["card security", "unauthorized card use", "fraudulent transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use app to freeze my card and dispute fraud?"

Keyphrases:
1439it [50:31,  2.20s/it]
ChatCompletion(id='chatcmpl-9MysVIVZk1aoP4LlGoaNiEIyfQMS6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["freeze card", "dispute fraud", "card security", "fraudulent transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264259, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=19, prompt_tokens=230, total_tokens=249))
["freeze card", "dispute fraud", "card security", "fraudulent transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone else is using my card, freeze it."

Keyphrases:
1440it [50:33,  2.13s/it]
ChatCompletion(id='chatcmpl-9MysYLMyeJdaMEIupo2RdTxo0Xzot', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card security", "freeze card", "unauthorized card use"]', role='assistant', function_call=None, tool_calls=None))], created=1715264262, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["card security", "freeze card", "unauthorized card use"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do all ATMs take this card?"

Keyphrases:
1441it [50:35,  1.93s/it]
ChatCompletion(id='chatcmpl-9Mysads7mVQcumiuRgxxUttg5ePfz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "card acceptance", "universal ATM access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264264, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["ATM compatibility", "card acceptance", "universal ATM access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Which ATMs accept this card?"

Keyphrases:
1442it [50:37,  2.02s/it]
ChatCompletion(id='chatcmpl-9Mysb6jd1R1VfEkNoaXwbiOzFePyh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "card-accepted ATMs", "usable ATMs"]', role='assistant', function_call=None, tool_calls=None))], created=1715264265, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=17, prompt_tokens=225, total_tokens=242))
["ATM compatibility", "card-accepted ATMs", "usable ATMs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is the closest Mastercard ATM?"

Keyphrases:
1443it [50:38,  1.78s/it]
ChatCompletion(id='chatcmpl-9MysdFgXG9kXqlCc68icxCkTVbcU3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["nearest ATM", "ATM location", "Mastercard ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715264267, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["nearest ATM", "ATM location", "Mastercard ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a list of ATM machines?"

Keyphrases:
1444it [50:40,  1.72s/it]
ChatCompletion(id='chatcmpl-9Myse9bjKYW1wXM7xJ2MZRamVIhMx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM locations", "find ATM", "nearest ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715264268, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["ATM locations", "find ATM", "nearest ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there any specific ATMs that this card can be used at?"

Keyphrases:
1445it [50:42,  1.82s/it]
ChatCompletion(id='chatcmpl-9MysgX2X4RsHc4njg6iwJsdntnoq3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "card accepted ATMs", "specific ATMs usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715264270, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=232, total_tokens=249))
["ATM compatibility", "card accepted ATMs", "specific ATMs usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I know which ATMs will accept this card?"

Keyphrases:
1446it [50:43,  1.61s/it]
ChatCompletion(id='chatcmpl-9MysiWKmkTuM9QtCZ87UYunjvgndQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "card acceptance", "ATM locations"]', role='assistant', function_call=None, tool_calls=None))], created=1715264272, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["ATM compatibility", "card acceptance", "ATM locations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Which ATM's accept my card?"

Keyphrases:
1447it [50:45,  1.84s/it]
ChatCompletion(id='chatcmpl-9MyskPZxdY7G1bpv08Ib6OcuIiXP5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "card accepted ATM locations", "ATM network"]', role='assistant', function_call=None, tool_calls=None))], created=1715264274, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["ATM compatibility", "card accepted ATM locations", "ATM network"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there any nearby ATM's?"

Keyphrases:
1448it [50:47,  1.78s/it]
ChatCompletion(id='chatcmpl-9MysmNHSaiJkliP2mTnfYvfnHSgKK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM location", "nearest ATM", "find ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715264276, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["ATM location", "nearest ATM", "find ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where are the locations of ATMs that accept this card?"

Keyphrases:
1449it [50:51,  2.41s/it]
ChatCompletion(id='chatcmpl-9MysnLzpFjecUKVItITogFL2ImYNY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM locations", "card-accepted ATMs", "ATM finder"]', role='assistant', function_call=None, tool_calls=None))], created=1715264277, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["ATM locations", "card-accepted ATMs", "ATM finder"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Which ATMs accept this placard ?"

Keyphrases:
1450it [50:52,  2.12s/it]
ChatCompletion(id='chatcmpl-9MysrCQJbbBI0la75p8RVfFwLhNyB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "placard accepted ATMs", "compatible ATMs"]', role='assistant', function_call=None, tool_calls=None))], created=1715264281, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=227, total_tokens=245))
["ATM compatibility", "placard accepted ATMs", "compatible ATMs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help me locate the nearest ATM."

Keyphrases:
1451it [50:54,  1.87s/it]
ChatCompletion(id='chatcmpl-9Mystf0ZzsOh2Rxz1UxX7DbKzmS9Q', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM locations", "nearest ATM", "find ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715264283, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["ATM locations", "nearest ATM", "find ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What ATMs is the card okay to use at?"

Keyphrases:
1452it [50:55,  1.80s/it]
ChatCompletion(id='chatcmpl-9MysupNYbMMEwAqzMdlgfM2TnGrfn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "accepted ATMs", "card usage at ATMs"]', role='assistant', function_call=None, tool_calls=None))], created=1715264284, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["ATM compatibility", "accepted ATMs", "card usage at ATMs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I find the nearest ATM?"

Keyphrases:
1453it [50:58,  2.18s/it]
ChatCompletion(id='chatcmpl-9MysvlnBCg3yK4e6lgxMKJGR9YhsN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["nearest ATM", "ATM location", "find ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715264285, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["nearest ATM", "ATM location", "find ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What kind of ATM's can I use?"

Keyphrases:
1454it [51:00,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyszJXxu1M5sNomF1kdv86R1N1XJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "ATM usage", "supported ATMs"]', role='assistant', function_call=None, tool_calls=None))], created=1715264289, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["ATM compatibility", "ATM usage", "supported ATMs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I withdraw money?"

Keyphrases:
1455it [51:01,  1.75s/it]
ChatCompletion(id='chatcmpl-9Myt06VwyIgjyfeKD80VNdLOFU6Xo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal process", "cash withdrawal", "ATM withdrawal"]', role='assistant', function_call=None, tool_calls=None))], created=1715264290, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["withdrawal process", "cash withdrawal", "ATM withdrawal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many miles away is the ATM?"

Keyphrases:
1456it [51:04,  2.20s/it]
ChatCompletion(id='chatcmpl-9Myt1sK3W3aR9EAEok8zXxFyRxOJg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM location", "nearest ATM", "distance to ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715264291, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["ATM location", "nearest ATM", "distance to ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "From where can I withdraw?"

Keyphrases:
1457it [51:06,  2.00s/it]
ChatCompletion(id='chatcmpl-9Myt4UK9li5ou4UEe4p0RRC2qLRrw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal locations", "ATM locations", "cash withdrawal points"]', role='assistant', function_call=None, tool_calls=None))], created=1715264294, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["withdrawal locations", "ATM locations", "cash withdrawal points"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Which ATM's will accept my card?"

Keyphrases:
1458it [51:07,  1.77s/it]
ChatCompletion(id='chatcmpl-9Myt6rKCOM35FJNv2cLGHIpwPgGYR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "card acceptance", "usable ATMs"]', role='assistant', function_call=None, tool_calls=None))], created=1715264296, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["ATM compatibility", "card acceptance", "usable ATMs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "At what ATMS am I able to use the card?"

Keyphrases:
1459it [51:08,  1.64s/it]
ChatCompletion(id='chatcmpl-9Myt7FuRMI60mudtnfSIoVgxxNA9H', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card ATM usage", "ATM compatibility", "usable ATMs"]', role='assistant', function_call=None, tool_calls=None))], created=1715264297, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["card ATM usage", "ATM compatibility", "usable ATMs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use my card at any ATMs?"

Keyphrases:
1460it [51:10,  1.61s/it]
ChatCompletion(id='chatcmpl-9Myt9MqIdtsCKWCOJkYBkgsdqpuJM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM usage", "card acceptance", "universal ATM access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264299, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["ATM usage", "card acceptance", "universal ATM access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get cash with this card anywhere?"

Keyphrases:
1461it [51:11,  1.61s/it]
ChatCompletion(id='chatcmpl-9MytA4oY5gWkYDqeMepMhf2EXJDi4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash access", "ATM compatibility", "universal card usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715264300, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["cash access", "ATM compatibility", "universal card usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "
Which ATMs accept this card?"

Keyphrases:
1462it [51:13,  1.53s/it]
ChatCompletion(id='chatcmpl-9MytCvS5NDHFLAUaV0Wf7KTPaxfA7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "accepted ATMs", "card usage at ATMs"]', role='assistant', function_call=None, tool_calls=None))], created=1715264302, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=17, prompt_tokens=225, total_tokens=242))
["ATM compatibility", "accepted ATMs", "card usage at ATMs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can someone please assist me with finding my nearest ATM?"

Keyphrases:
1463it [51:14,  1.44s/it]
ChatCompletion(id='chatcmpl-9MytDXj42Re2dsnRh2FvLwTrbq2oS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM location", "nearest ATM", "find ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715264303, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["ATM location", "nearest ATM", "find ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there any ATM machines near me?"

Keyphrases:
1464it [51:17,  1.94s/it]
ChatCompletion(id='chatcmpl-9MytErV5sBybDVz5YZ6HvOWSOo5ga', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM location", "nearest ATM", "ATM finder"]', role='assistant', function_call=None, tool_calls=None))], created=1715264304, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["ATM location", "nearest ATM", "ATM finder"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is the nearest bank machine?"

Keyphrases:
1465it [51:18,  1.70s/it]
ChatCompletion(id='chatcmpl-9MytHzI6NxzTq2dStjxnhnWsVx0tw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM location", "nearest bank machine", "find ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715264307, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["ATM location", "nearest bank machine", "find ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What type of ATMs accept this card?"

Keyphrases:
1466it [51:22,  2.25s/it]
ChatCompletion(id='chatcmpl-9MytJHZksTnlRWXdsJHLPQQICSOIJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "card acceptance", "usable ATMs"]', role='assistant', function_call=None, tool_calls=None))], created=1715264309, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["ATM compatibility", "card acceptance", "usable ATMs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I use this card at an ATM?"

Keyphrases:
1467it [51:23,  2.07s/it]
ChatCompletion(id='chatcmpl-9MytMelxplz42Fcc5DfRPrjhS39ws', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM locations", "card usage", "ATM compatibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715264312, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["ATM locations", "card usage", "ATM compatibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I have this card, which ATMs can I go to?"

Keyphrases:
1468it [51:26,  2.10s/it]
ChatCompletion(id='chatcmpl-9MytOV1c65BdqI1BHacsj4JioOl9x', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "card accepted ATMs", "ATM network"]', role='assistant', function_call=None, tool_calls=None))], created=1715264314, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["ATM compatibility", "card accepted ATMs", "ATM network"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What ATMs can I withdraw money from?"

Keyphrases:
1469it [51:28,  2.08s/it]
ChatCompletion(id='chatcmpl-9MytQqgZCm2SV6y5PUgdR38eBLQnd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM locations", "withdrawal points", "ATM network access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264316, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["ATM locations", "withdrawal points", "ATM network access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to withdraw money, where can I go?"

Keyphrases:
1470it [51:29,  1.85s/it]
ChatCompletion(id='chatcmpl-9MytSnKu0LEnuxZDQCpX4digVFGw0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal locations", "ATM locations", "cash withdrawal points"]', role='assistant', function_call=None, tool_calls=None))], created=1715264318, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["withdrawal locations", "ATM locations", "cash withdrawal points"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I withdrawal my money?"

Keyphrases:
1471it [51:31,  1.85s/it]
ChatCompletion(id='chatcmpl-9MytTMsZGIwbX3AJs1Yq0errUo9z1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal locations", "ATM locations", "money withdrawal"]', role='assistant', function_call=None, tool_calls=None))], created=1715264319, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["withdrawal locations", "ATM locations", "money withdrawal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the ATMs that will accept this card?"

Keyphrases:
1472it [51:32,  1.79s/it]
ChatCompletion(id='chatcmpl-9MytVeigIKKueX13VIflKVXCBYFYE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "card acceptance", "ATM locations"]', role='assistant', function_call=None, tool_calls=None))], created=1715264321, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["ATM compatibility", "card acceptance", "ATM locations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What ATMs will accept this type of card?"

Keyphrases:
1473it [51:34,  1.69s/it]
ChatCompletion(id='chatcmpl-9MytXkKUIQHjJAtZbpCJ5NuWJyfR9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "card acceptance", "compatible ATMs"]', role='assistant', function_call=None, tool_calls=None))], created=1715264323, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["ATM compatibility", "card acceptance", "compatible ATMs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I find an ATM to use this card?"

Keyphrases:
1474it [51:36,  1.66s/it]
ChatCompletion(id='chatcmpl-9MytYWSGbzKpK5u9ksTKUh5i1nikc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM locations", "nearest ATM", "card-compatible ATMs"]', role='assistant', function_call=None, tool_calls=None))], created=1715264324, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["ATM locations", "nearest ATM", "card-compatible ATMs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "At which ATMs can I use this card?"

Keyphrases:
1475it [51:37,  1.63s/it]
ChatCompletion(id='chatcmpl-9MytanRlLaraAg6h19gja3Vrh2ltB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card-compatible ATMs", "ATM usage", "ATM locations"]', role='assistant', function_call=None, tool_calls=None))], created=1715264326, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["card-compatible ATMs", "ATM usage", "ATM locations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there certain ATMs that I can use this card at?"

Keyphrases:
1476it [51:39,  1.66s/it]
ChatCompletion(id='chatcmpl-9MytbMRUM5rYITHhYL8mRMD8B1BFR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM compatibility", "card usage", "specific ATMs"]', role='assistant', function_call=None, tool_calls=None))], created=1715264327, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["ATM compatibility", "card usage", "specific ATMs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you know the closest ATM?"

Keyphrases:
1477it [51:40,  1.55s/it]
ChatCompletion(id='chatcmpl-9Mytd25xKIpZ09eqmo3NY3WsRy75C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["nearest ATM", "ATM location", "find ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715264329, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["nearest ATM", "ATM location", "find ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use this card at an ATM?"

Keyphrases:
1478it [51:41,  1.47s/it]
ChatCompletion(id='chatcmpl-9MytePw0o4W4fmAPfgbFTfgnqVHOu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM usage", "card access", "using card at ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715264330, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["ATM usage", "card access", "using card at ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there places where I can't withdraw money?"

Keyphrases:
1479it [51:43,  1.51s/it]
ChatCompletion(id='chatcmpl-9MytgEXBmYsUmFjpaqjrdJjvQdJQI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal restrictions", "ATM limitations", "restricted withdrawal areas"]', role='assistant', function_call=None, tool_calls=None))], created=1715264332, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["withdrawal restrictions", "ATM limitations", "restricted withdrawal areas"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "locations to withdraw money"

Keyphrases:
1480it [51:44,  1.40s/it]
ChatCompletion(id='chatcmpl-9Mythnds7GcrZu3mVIdHMgYRKfELN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM locations", "withdrawal points", "money withdrawal sites"]', role='assistant', function_call=None, tool_calls=None))], created=1715264333, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=223, total_tokens=238))
["ATM locations", "withdrawal points", "money withdrawal sites"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help me.  There is a Direct Debit that I didn't make."

Keyphrases:
1481it [51:47,  1.80s/it]
ChatCompletion(id='chatcmpl-9MytiCnXZN15EL50koTwEVhZX8U40', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized debit", "fraudulent transaction", "report unauthorized charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715264334, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=234, total_tokens=250))
["unauthorized debit", "fraudulent transaction", "report unauthorized charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a direct debit that's not mine."

Keyphrases:
1482it [51:49,  1.88s/it]
ChatCompletion(id='chatcmpl-9MytltKGlJeI4Ep32PCFzih25HBHJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized debit", "fraudulent transaction", "direct debit issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264337, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["unauthorized debit", "fraudulent transaction", "direct debit issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a strange direct debit in my statement"

Keyphrases:
1483it [51:50,  1.69s/it]
ChatCompletion(id='chatcmpl-9MytndzuoC3gkugYwvxqhQN9CZZJi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized debit", "account discrepancy", "fraudulent transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264339, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["unauthorized debit", "account discrepancy", "fraudulent transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't understand where this debit came from and want it removed."

Keyphrases:
1484it [51:52,  1.61s/it]
ChatCompletion(id='chatcmpl-9Mytpc4PMZsnbK0Kegyoki1LDoU5P', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized debit", "dispute transaction", "remove charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715264341, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["unrecognized debit", "dispute transaction", "remove charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what is this charge on my account"

Keyphrases:
1485it [51:53,  1.65s/it]
ChatCompletion(id='chatcmpl-9MytqIPOkIc0GIatyG4uQDBkfF9r1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized charge", "account charge query", "dispute charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715264342, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["unrecognized charge", "account charge query", "dispute charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "im so mad right now. theres several charges that I think my x boyfriend made on my card. the companys on the website wouldn't refund me my money, they told me to contact my bank. DO something please."

Keyphrases:
1486it [51:55,  1.69s/it]
ChatCompletion(id='chatcmpl-9Mytsz4mjCb7XUfXL3sULzrlVdnDi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized charges", "dispute transaction", "fraudulent charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715264344, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=263, total_tokens=279))
["unauthorized charges", "dispute transaction", "fraudulent charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "someone stole my money"

Keyphrases:
1487it [51:57,  1.67s/it]
ChatCompletion(id='chatcmpl-9Mytt7ApQlwysRx6KXulAu4dEnxsa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["theft report", "stolen money", "fraud report"]', role='assistant', function_call=None, tool_calls=None))], created=1715264345, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=223, total_tokens=238))
["theft report", "stolen money", "fraud report"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There's a Direct Debit payment in my account that I didn't make"

Keyphrases:
1488it [51:58,  1.68s/it]
ChatCompletion(id='chatcmpl-9MytvBJVUqDGIywJzXGZB1ITSIiyv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized payment", "Direct Debit issue", "fraudulent transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264347, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=234, total_tokens=251))
["unauthorized payment", "Direct Debit issue", "fraudulent transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There's a debit on my account that I didn't do."

Keyphrases:
1489it [52:00,  1.64s/it]
ChatCompletion(id='chatcmpl-9MytxBsh7z97gONzKcSq5xj4pkl5P', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized debit", "fraudulent transaction", "unrecognized charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715264349, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["unauthorized debit", "fraudulent transaction", "unrecognized charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I may have a fraud charge on my debit statement."

Keyphrases:
1490it [52:01,  1.52s/it]
ChatCompletion(id='chatcmpl-9Myty5Eqyq1tkdMrpPkUpOTOkh6u5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fraudulent charge", "debit card fraud", "unauthorized transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264350, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["fraudulent charge", "debit card fraud", "unauthorized transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is there a direct debit payment on my app that is not from me?"

Keyphrases:
1491it [52:03,  1.59s/it]
ChatCompletion(id='chatcmpl-9Myu0QmF0mq1PZ7uvjLAIFjyYRTI6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraudulent charge", "direct debit issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264352, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=234, total_tokens=250))
["unauthorized transaction", "fraudulent charge", "direct debit issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Weird charges are appearing in my debit account."

Keyphrases:
1492it [52:05,  1.68s/it]
ChatCompletion(id='chatcmpl-9Myu1QQycEtcHsRLviuiEYlZxA1pF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized charges", "fraudulent transaction", "dispute charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715264353, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["unrecognized charges", "fraudulent transaction", "dispute charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Even though it's late, I wanted to see about disputing a charge. I was just looking through my transactions over the past couple of months and noticed a pretty large amount that was not completed by me. Is this possibly something I can still do."

Keyphrases:
1493it [52:06,  1.57s/it]
ChatCompletion(id='chatcmpl-9Myu35ZQJIQnDx41PFN5Hi9mMnbxX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["dispute charge", "unauthorized transaction", "chargeback request"]', role='assistant', function_call=None, tool_calls=None))], created=1715264355, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=269, total_tokens=284))
["dispute charge", "unauthorized transaction", "chargeback request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There was a transaction from two weeks ago from a business that I don't know. I'm fairly certain it wasn't me who made it, but is it an option to trace it to confirm?"

Keyphrases:
1494it [52:08,  1.51s/it]
ChatCompletion(id='chatcmpl-9Myu4fh5tWxS4dXJ5PuBktTE9TQ1k', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "transaction trace", "fraud investigation"]', role='assistant', function_call=None, tool_calls=None))], created=1715264356, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=258, total_tokens=272))
["unrecognized transaction", "transaction trace", "fraud investigation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is this direct debit I am seeing?"

Keyphrases:
1495it [52:09,  1.49s/it]
ChatCompletion(id='chatcmpl-9Myu6h5LelVwhJfBAwAFZSiRodMPn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["direct debit inquiry", "unknown transaction", "transaction details"]', role='assistant', function_call=None, tool_calls=None))], created=1715264358, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["direct debit inquiry", "unknown transaction", "transaction details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a Direct Debit that I don't recognize."

Keyphrases:
1496it [52:10,  1.44s/it]
ChatCompletion(id='chatcmpl-9Myu79skiU0VHG84o3ZhdZb2TzXO6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "Direct Debit issue", "fraudulent transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264359, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["unrecognized transaction", "Direct Debit issue", "fraudulent transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Unknown direct deposit"

Keyphrases:
1497it [52:12,  1.39s/it]
ChatCompletion(id='chatcmpl-9Myu9o4KhWrVpWZ3QmQN8erjhDXQh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["direct deposit issue", "deposit not recognized", "unidentified deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715264361, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=222, total_tokens=237))
["direct deposit issue", "deposit not recognized", "unidentified deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a suspicious direct debit payment."

Keyphrases:
1498it [52:13,  1.48s/it]
ChatCompletion(id='chatcmpl-9MyuAJIsgtOxj95DPIwi3AdTNIxPr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["suspicious debit", "unauthorized transaction", "fraudulent payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715264362, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["suspicious debit", "unauthorized transaction", "fraudulent payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a transaction from my account that I don't recognize can you trace back the information so I can make sure it's something I did or not?"

Keyphrases:
1499it [52:15,  1.50s/it]
ChatCompletion(id='chatcmpl-9MyuCj0cP36ddFMtc863V2d0YPWYE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "transaction trace", "fraud investigation"]', role='assistant', function_call=None, tool_calls=None))], created=1715264364, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=249, total_tokens=263))
["unrecognized transaction", "transaction trace", "fraud investigation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "A couple weeks ago some money was deducted from my account by some seller that I don't remember. I'm pretty sure I didn't do that, but is it possible to trace back who that is just to make sure?"

Keyphrases:
1500it [52:16,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyuDpH1IqTurdcZSWPRhO8PURAkx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "trace transaction", "seller identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715264365, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=263, total_tokens=276))
["unauthorized transaction", "trace transaction", "seller identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I found a charge for a direct debit that was not made by me."

Keyphrases:
1501it [52:18,  1.48s/it]
ChatCompletion(id='chatcmpl-9MyuEHHafVkFokH74BCV8VBG6svxo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized debit", "fraudulent charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264366, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["unauthorized debit", "fraudulent charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am seeing a weird payment showing up that I know I did not make, how can I get it cancelled?"

Keyphrases:
1502it [52:19,  1.49s/it]
ChatCompletion(id='chatcmpl-9MyuGyJfEWogikVPC2lk0gpFQqcS8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized payment", "fraudulent transaction", "cancel payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715264368, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=241, total_tokens=256))
["unauthorized payment", "fraudulent transaction", "cancel payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "This Direct Debit payment may not be right."

Keyphrases:
1503it [52:21,  1.50s/it]
ChatCompletion(id='chatcmpl-9MyuIyos7IMIwaZ49Zew4e2L30EhJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["direct debit issue", "payment dispute", "incorrect charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715264370, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["direct debit issue", "payment dispute", "incorrect charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "why does the app show a direct debit payment that I did not authorize"

Keyphrases:
1504it [52:22,  1.45s/it]
ChatCompletion(id='chatcmpl-9MyuJ5oX9GnLSuMyFRWwtRCqBF7MG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized payment", "direct debit issue", "payment dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715264371, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["unauthorized payment", "direct debit issue", "payment dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I dispute a payment even if I notice it several weeks after it was made?"

Keyphrases:
1505it [52:25,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyuKjvcSEypEPDO21F9XjFypv8sf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["dispute payment", "late payment dispute", "payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264372, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["dispute payment", "late payment dispute", "payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It seems there is an incorrect listing of a direct debit payment on my app that I did not make"

Keyphrases:
1506it [52:26,  1.74s/it]
ChatCompletion(id='chatcmpl-9MyuNunuqnqgblbnsJkUczZyXzdEB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized debit", "incorrect direct debit", "fraudulent transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264375, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=239, total_tokens=255))
["unauthorized debit", "incorrect direct debit", "fraudulent transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't think I made this charge on my debit statement."

Keyphrases:
1507it [52:28,  1.72s/it]
ChatCompletion(id='chatcmpl-9MyuPYW1a4J86EtdgGvKRdrfSth1B', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized charge", "dispute transaction", "fraudulent charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715264377, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["unrecognized charge", "dispute transaction", "fraudulent charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a direct debit charge that I do not recognize"

Keyphrases:
1508it [52:31,  2.10s/it]
ChatCompletion(id='chatcmpl-9MyuQ0Wcm0Tq0vogzuHd6CMlaYIEi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized charge", "direct debit issue", "query charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715264378, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["unrecognized charge", "direct debit issue", "query charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I didn't make this direct debit transaction"

Keyphrases:
1509it [52:33,  2.09s/it]
ChatCompletion(id='chatcmpl-9MyuT7nuAa0ASb4c26JCeE4AVGzhK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "dispute transaction", "fraudulent debit"]', role='assistant', function_call=None, tool_calls=None))], created=1715264381, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["unauthorized transaction", "dispute transaction", "fraudulent debit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There's a direct debit on my account that I didn't authorize"

Keyphrases:
1510it [52:34,  1.88s/it]
ChatCompletion(id='chatcmpl-9MyuVtkR8hJhHGWCC50UZKfNC0guW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "direct debit issue", "fraudulent transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264383, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["unauthorized transaction", "direct debit issue", "fraudulent transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I understand that this is extremely late. After going over my transactions for the last couple of months I noticed a large charge that I'm sure I did not make. Is there anyway I can still dispute this?"

Keyphrases:
1511it [52:36,  1.78s/it]
ChatCompletion(id='chatcmpl-9MyuXDdxM2g1qxZbW9PchuoWY8rBD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["dispute transaction", "unauthorized charge", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264385, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=260, total_tokens=274))
["dispute transaction", "unauthorized charge", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't recognize a debit payment that was made and would like to find out about the payment."

Keyphrases:
1512it [52:38,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyuY4YN0WWh0OAS51802jKSGF43d', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized payment", "dispute transaction", "payment inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715264386, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=238, total_tokens=252))
["unrecognized payment", "dispute transaction", "payment inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am concerned about the security in my account and would like to make a dispute."

Keyphrases:
1513it [52:41,  2.14s/it]
ChatCompletion(id='chatcmpl-9Myua8hfpA0yEkXoE0EDXese4vg2B', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account security", "dispute", "security concern"]', role='assistant', function_call=None, tool_calls=None))], created=1715264388, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=235, total_tokens=247))
["account security", "dispute", "security concern"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is there a direct debit I didn't make showing in the app?"

Keyphrases:
1514it [52:42,  2.00s/it]
ChatCompletion(id='chatcmpl-9MyudyU6A6E9zhzjfTBmqIEZrXU5I', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraudulent charge", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264391, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["unauthorized transaction", "fraudulent charge", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a direct debit I do not recognise in my statement"

Keyphrases:
1515it [52:46,  2.47s/it]
ChatCompletion(id='chatcmpl-9MyugCRRKcnZS4WUVaPgkW1ZM4mvX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "dispute transaction", "direct debit issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264394, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["unrecognized transaction", "dispute transaction", "direct debit issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a direct debit transaction I have not set up, but would like to ."

Keyphrases:
1516it [52:48,  2.37s/it]
ChatCompletion(id='chatcmpl-9MyuiVgZ0eUlpkehavMtnVMR139du', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["set up direct debit", "initiate direct debit", "direct debit setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715264396, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=236, total_tokens=253))
["set up direct debit", "initiate direct debit", "direct debit setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone has taken my money and I don't know who"

Keyphrases:
1517it [52:50,  2.09s/it]
ChatCompletion(id='chatcmpl-9MyukkfF2bi0pftImWvx0g1VVRGRB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraud detection", "missing funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715264398, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["unauthorized transaction", "fraud detection", "missing funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was charged on my account that shouldn't be there."

Keyphrases:
1518it [52:52,  2.10s/it]
ChatCompletion(id='chatcmpl-9Myum62ZSaHEf8I6dRzKMUHzhE1cf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized charge", "dispute transaction", "fraudulent charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715264400, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["unauthorized charge", "dispute transaction", "fraudulent charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There's a direct debit I wish to dispute"

Keyphrases:
1519it [52:53,  1.91s/it]
ChatCompletion(id='chatcmpl-9Myuo9iphL4UvyAMMZFHtFOX1zJZi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["dispute direct debit", "question charge", "unauthorized transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264402, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["dispute direct debit", "question charge", "unauthorized transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was my account deducted from a seller when I didn't approve of it?"

Keyphrases:
1520it [52:55,  1.80s/it]
ChatCompletion(id='chatcmpl-9MyuqqpHvikhHak4qfI7qq1zNOwXJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraudulent deduction", "unapproved charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715264404, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=234, total_tokens=250))
["unauthorized transaction", "fraudulent deduction", "unapproved charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do if I forget my passcode?  Because I did."

Keyphrases:
1521it [52:57,  1.87s/it]
ChatCompletion(id='chatcmpl-9MyurnULXr3yjjBYJbncrzw3DNeTH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "forgotten passcode", "account access recovery"]', role='assistant', function_call=None, tool_calls=None))], created=1715264405, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=234, total_tokens=250))
["reset passcode", "forgotten passcode", "account access recovery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't find my password"

Keyphrases:
1522it [52:58,  1.68s/it]
ChatCompletion(id='chatcmpl-9MyutdPOX8TkpOsls50hJl8ZrN1Cy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["password recovery", "reset password", "lost password"]', role='assistant', function_call=None, tool_calls=None))], created=1715264407, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["password recovery", "reset password", "lost password"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I retrieve my passcode?"

Keyphrases:
1523it [53:00,  1.74s/it]
ChatCompletion(id='chatcmpl-9Myuu5DAyGmOqTthjHgppddCu0Dpj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["retrieve passcode", "forgotten passcode", "reset passcode"]', role='assistant', function_call=None, tool_calls=None))], created=1715264408, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["retrieve passcode", "forgotten passcode", "reset passcode"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My passcode doesn't seem to be working"

Keyphrases:
1524it [53:01,  1.67s/it]
ChatCompletion(id='chatcmpl-9MyuwMLq8vg2y54qcH6p3Kf4E0zTf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["passcode issue", "passcode not working", "authentication problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264410, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["passcode issue", "passcode not working", "authentication problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I lost my password"

Keyphrases:
1525it [53:04,  1.84s/it]
ChatCompletion(id='chatcmpl-9MyuyAVfUmQjCxrLmS9vOxOc2EUjO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["password reset", "lost password", "account recovery"]', role='assistant', function_call=None, tool_calls=None))], created=1715264412, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["password reset", "lost password", "account recovery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My password isn't being accepted and I need to reset it."

Keyphrases:
1526it [53:06,  1.86s/it]
ChatCompletion(id='chatcmpl-9Myv0mr0pGgjmkSXkUWF9ffEVs3rx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["password reset", "account access issue", "reset password procedures"]', role='assistant', function_call=None, tool_calls=None))], created=1715264414, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["password reset", "account access issue", "reset password procedures"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Something is wrong with my password."

Keyphrases:
1527it [53:07,  1.67s/it]
ChatCompletion(id='chatcmpl-9Myv2ApqXeoxayjxk8qc5eY3q1QH7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["password issue", "reset password", "login problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264416, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["password issue", "reset password", "login problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Something is wrong with my passcode"

Keyphrases:
1528it [53:08,  1.61s/it]
ChatCompletion(id='chatcmpl-9Myv3NpbQNpVOoLT0vQaWutbv3a0p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["passcode issues", "reset passcode", "incorrect passcode"]', role='assistant', function_call=None, tool_calls=None))], created=1715264417, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["passcode issues", "reset passcode", "incorrect passcode"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I reset a forgotten passcode, please?"

Keyphrases:
1529it [53:10,  1.76s/it]
ChatCompletion(id='chatcmpl-9Myv5KsU6KpBo2SXChoMJaXR5qOtX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "forgot passcode", "password recovery"]', role='assistant', function_call=None, tool_calls=None))], created=1715264419, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["reset passcode", "forgot passcode", "password recovery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't recall my passcode and need to reset it."

Keyphrases:
1530it [53:12,  1.86s/it]
ChatCompletion(id='chatcmpl-9Myv7ZzOw60ZgAlckX0xJjxoQxrSY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "forgot passcode", "passcode recovery"]', role='assistant', function_call=None, tool_calls=None))], created=1715264421, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["reset passcode", "forgot passcode", "passcode recovery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I be given a new passcode?"

Keyphrases:
1531it [53:14,  1.73s/it]
ChatCompletion(id='chatcmpl-9Myv9MgqjlXNjO0SZ928UlSSdq7Ze', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "new passcode", "password reset"]', role='assistant', function_call=None, tool_calls=None))], created=1715264423, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["reset passcode", "new passcode", "password reset"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I do not know my passcode."

Keyphrases:
1532it [53:16,  1.90s/it]
ChatCompletion(id='chatcmpl-9MyvAdD34SS4Hy72E5eZ23ejkFDp1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["forgotten passcode", "reset passcode", "passcode recovery"]', role='assistant', function_call=None, tool_calls=None))], created=1715264424, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["forgotten passcode", "reset passcode", "passcode recovery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't remember my code to get into the app."

Keyphrases:
1533it [53:20,  2.61s/it]
ChatCompletion(id='chatcmpl-9MyvDayFWarCOGi0juRu5ERhrpKHR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["forgot code", "reset code", "access code recovery"]', role='assistant', function_call=None, tool_calls=None))], created=1715264427, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["forgot code", "reset code", "access code recovery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I no longer have my passcode."

Keyphrases:
1534it [53:26,  3.49s/it]
ChatCompletion(id='chatcmpl-9MyvHtCCLxGNbjkn9prQUuv9HtSSP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost passcode", "reset passcode", "forgot passcode"]', role='assistant', function_call=None, tool_calls=None))], created=1715264431, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["lost passcode", "reset passcode", "forgot passcode"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why won't my passcode work?"

Keyphrases:
1535it [53:27,  2.80s/it]
ChatCompletion(id='chatcmpl-9MyvM35p5N643jhqnbvot5TNaBQlf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["passcode issue", "authentication problem", "login failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715264436, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["passcode issue", "authentication problem", "login failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I resent my passcode?"

Keyphrases:
1536it [53:29,  2.61s/it]
ChatCompletion(id='chatcmpl-9MyvOQfjKrwF60pr48bMZaaEnCcRS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "passcode issue", "change passcode"]', role='assistant', function_call=None, tool_calls=None))], created=1715264438, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["reset passcode", "passcode issue", "change passcode"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to reset my passcode. How do I do it?"

Keyphrases:
1537it [53:31,  2.38s/it]
ChatCompletion(id='chatcmpl-9MyvQ3j2l3ib1tvwgwP4mOFNuwdJx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "passcode change", "password reset"]', role='assistant', function_call=None, tool_calls=None))], created=1715264440, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["reset passcode", "passcode change", "password reset"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Show me please how to reset my passcode."

Keyphrases:
1538it [53:33,  2.28s/it]
ChatCompletion(id='chatcmpl-9MyvSqSY9QNQ1yBWK91dCCA71CkKn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "change password", "passcode update"]', role='assistant', function_call=None, tool_calls=None))], created=1715264442, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["reset passcode", "change password", "passcode update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help me reset the passcode."

Keyphrases:
1539it [53:35,  2.15s/it]
ChatCompletion(id='chatcmpl-9MyvUYrdsXgJUyKrFvdE5HCPzsrD7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "forgot passcode", "change passcode"]', role='assistant', function_call=None, tool_calls=None))], created=1715264444, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["reset passcode", "forgot passcode", "change passcode"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have forgotten my passcode to access my app"

Keyphrases:
1540it [53:37,  2.09s/it]
ChatCompletion(id='chatcmpl-9MyvVoP9tVevjmGbwPyAJl65dk5V0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["forgotten passcode", "reset passcode", "app access issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264445, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["forgotten passcode", "reset passcode", "app access issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What should I do if the passcode doesn't work for me?"

Keyphrases:
1541it [53:38,  1.83s/it]
ChatCompletion(id='chatcmpl-9MyvXRwCAlMPGgDnAjtYnnQgxKArT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["passcode issues", "reset passcode", "authentication problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264447, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["passcode issues", "reset passcode", "authentication problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I do not remember the code, what should I do?"

Keyphrases:
1542it [53:40,  1.69s/it]
ChatCompletion(id='chatcmpl-9MyvZ2leDU6DWXpTR36tQpffOpOHb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["forgotten code", "reset code", "code recovery"]', role='assistant', function_call=None, tool_calls=None))], created=1715264449, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["forgotten code", "reset code", "code recovery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I reset the passcode?"

Keyphrases:
1543it [53:41,  1.59s/it]
ChatCompletion(id='chatcmpl-9MyvasHgqRR2HshxzOgGOu4G7RbpF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "password reset location", "change passcode"]', role='assistant', function_call=None, tool_calls=None))], created=1715264450, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["reset passcode", "password reset location", "change passcode"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need help resetting my passcode to access my app."

Keyphrases:
1544it [53:42,  1.54s/it]
ChatCompletion(id='chatcmpl-9Myvb6AF8HodWMKda6PitDZKbg2JW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "passcode assistance", "account access help"]', role='assistant', function_call=None, tool_calls=None))], created=1715264451, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["reset passcode", "passcode assistance", "account access help"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What steps do I take to receive another passcode?"

Keyphrases:
1545it [53:44,  1.50s/it]
ChatCompletion(id='chatcmpl-9Myvd5OcWG4a3la0hKenBKSDZs6mT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "new passcode", "passcode issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264453, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["reset passcode", "new passcode", "passcode issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I forgot my password"

Keyphrases:
1546it [53:47,  2.00s/it]
ChatCompletion(id='chatcmpl-9MyveKcHQdUsBkk2hPm2xYWOGc7nv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["password reset", "forgot password", "account access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264454, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["password reset", "forgot password", "account access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I forgot my code to get into the app."

Keyphrases:
1547it [53:49,  1.92s/it]
ChatCompletion(id='chatcmpl-9MyvhIlvhdx4ltb7Zr4GTGjyFHL4h', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["forgotten code", "reset access code", "account access issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264457, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["forgotten code", "reset access code", "account access issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have forgotten my password."

Keyphrases:
1548it [53:51,  2.02s/it]
ChatCompletion(id='chatcmpl-9Myvjb09IPM4g8FLLkORDZGOM5Cmo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["password reset", "forgot password", "account access recovery"]', role='assistant', function_call=None, tool_calls=None))], created=1715264459, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["password reset", "forgot password", "account access recovery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I forgot the code to access the app."

Keyphrases:
1549it [53:52,  1.84s/it]
ChatCompletion(id='chatcmpl-9MyvlIVxOgP0AGOin78lC9e4Sm0V2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["access code", "forgot password", "app login issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264461, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["access code", "forgot password", "app login issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a way to reset my passcode?"

Keyphrases:
1550it [53:55,  1.94s/it]
ChatCompletion(id='chatcmpl-9MyvnnTJdFsn5rsIpc1Cz3H0S1wIN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "forgot passcode", "change passcode"]', role='assistant', function_call=None, tool_calls=None))], created=1715264463, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["reset passcode", "forgot passcode", "change passcode"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you help me reset my password?"

Keyphrases:
1551it [53:57,  1.94s/it]
ChatCompletion(id='chatcmpl-9MyvpDpybpp7mDpWnZy6M5dEQ595Y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["password reset", "account security", "change password"]', role='assistant', function_call=None, tool_calls=None))], created=1715264465, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["password reset", "account security", "change password"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I reset my password?  I don't know what it is."

Keyphrases:
1552it [54:01,  2.69s/it]
ChatCompletion(id='chatcmpl-9Myvr62OZtCTJ0FHfUNnuAxFY9Eiz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["password reset", "forgot password", "account access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264467, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=233, total_tokens=245))
["password reset", "forgot password", "account access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I reset the passcode?"

Keyphrases:
1553it [54:03,  2.37s/it]
ChatCompletion(id='chatcmpl-9MyvvYCFjPrh5wUhE99NgHMnLdXmc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "password reset", "change passcode"]', role='assistant', function_call=None, tool_calls=None))], created=1715264471, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["reset passcode", "password reset", "change passcode"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What should I do if I forgot my passcode?"

Keyphrases:
1554it [54:04,  2.05s/it]
ChatCompletion(id='chatcmpl-9MyvxfQoRg8vj3MpAkeDQdYzeGhMv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["forgot passcode", "reset passcode", "account access recovery"]', role='assistant', function_call=None, tool_calls=None))], created=1715264473, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["forgot passcode", "reset passcode", "account access recovery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My passcode doesn't work"

Keyphrases:
1555it [54:06,  2.10s/it]
ChatCompletion(id='chatcmpl-9MyvympAwPEETuL4iBgprZwU5QeaA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["passcode issue", "reset passcode", "authentication problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264474, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["passcode issue", "reset passcode", "authentication problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Tell me how to reset the passcode."

Keyphrases:
1556it [54:07,  1.79s/it]
ChatCompletion(id='chatcmpl-9Myw0VTiIsCPknrtcgumFTEiRZ5Qh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "change password", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715264476, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["reset passcode", "change password", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need a new passcode."

Keyphrases:
1557it [54:10,  2.22s/it]
ChatCompletion(id='chatcmpl-9Myw2L7iRBXlbTC6YCTVnU100wO4n', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "new passcode", "change passcode"]', role='assistant', function_call=None, tool_calls=None))], created=1715264478, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["reset passcode", "new passcode", "change passcode"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't have my access code for the app."

Keyphrases:
1558it [54:12,  2.00s/it]
ChatCompletion(id='chatcmpl-9Myw5JFYrLuLYsmThqz9ZBfZffoVc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["access code", "login issue", "app access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264481, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["access code", "login issue", "app access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me what to do to reset my passcode?"

Keyphrases:
1559it [54:13,  1.80s/it]
ChatCompletion(id='chatcmpl-9Myw6rSybEvqlLfyWyVAhsiNxJTuS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reset passcode", "password recovery", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715264482, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["reset passcode", "password recovery", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the code I need to get into the app?"

Keyphrases:
1560it [54:16,  2.06s/it]
ChatCompletion(id='chatcmpl-9Myw798Vwoy3HhYV0krBxutkb0mX7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["app access code", "login code", "authentication code"]', role='assistant', function_call=None, tool_calls=None))], created=1715264483, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["app access code", "login code", "authentication code"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me why you won't let me get my own money out of the money machine? I know I used the right PIN."

Keyphrases:
1561it [54:17,  1.90s/it]
ChatCompletion(id='chatcmpl-9MywAVgvqVvZi9Bqcdxti8PW79E6f', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "denied withdrawal", "correct PIN but denied"]', role='assistant', function_call=None, tool_calls=None))], created=1715264486, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=246, total_tokens=263))
["ATM withdrawal issue", "denied withdrawal", "correct PIN but denied"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My withdrawal was cancelled."

Keyphrases:
1562it [54:20,  2.10s/it]
ChatCompletion(id='chatcmpl-9MywC6exN1l8AWSnGtz9lE02SCfOs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal issue", "cancelled withdrawal", "transaction problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264488, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["withdrawal issue", "cancelled withdrawal", "transaction problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "This is very frustrating. I can't get my card to work on any ATM I try and I've tried 3 of them so far. What's going on? Can you please fix this issue immediately?"

Keyphrases:
1563it [54:22,  2.02s/it]
ChatCompletion(id='chatcmpl-9MywEVxdT5KLnr2QojEReMZWcyoyK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "ATM issue", "card not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715264490, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=260, total_tokens=274))
["card malfunction", "ATM issue", "card not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM did not allow me to withdraw"

Keyphrases:
1564it [54:24,  1.98s/it]
ChatCompletion(id='chatcmpl-9MywGDhUxJT00WFbjv7faTUm8HXJH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "withdrawal problem", "ATM access error"]', role='assistant', function_call=None, tool_calls=None))], created=1715264492, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=227, total_tokens=244))
["ATM withdrawal issue", "withdrawal problem", "ATM access error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was my ATM transaction cancelled?"

Keyphrases:
1565it [54:27,  2.47s/it]
ChatCompletion(id='chatcmpl-9MywIArmv2NjfuG7yiynB8RplDBQy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM transaction", "transaction cancellation", "cancelled transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264494, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["ATM transaction", "transaction cancellation", "cancelled transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM keeps declining my card. I tried at a couple different ATMs. Can you tell me if there's a problem with my account?"

Keyphrases:
1566it [54:29,  2.17s/it]
ChatCompletion(id='chatcmpl-9MywMXKeTreTjwuwB1nZV5kwzltDw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card decline", "multiple ATMs", "account problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264498, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=247, total_tokens=262))
["ATM card decline", "multiple ATMs", "account problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was at the ATM trying to made a withdraw and I was declined."

Keyphrases:
1567it [54:31,  2.07s/it]
ChatCompletion(id='chatcmpl-9MywNkbg4cqvhRWqNkmGh7f8amROT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "declined transaction", "withdrawal problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264499, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["ATM withdrawal issue", "declined transaction", "withdrawal problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM didn't let me get any cash"

Keyphrases:
1568it [54:33,  2.05s/it]
ChatCompletion(id='chatcmpl-9MywPaxcyV5GlJGUJKhspSrr8hArD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "cash withdrawal problem", "ATM malfunction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264501, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["ATM withdrawal issue", "cash withdrawal problem", "ATM malfunction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to know why I have been unable to withdrawn funds."

Keyphrases:
1569it [54:34,  1.89s/it]
ChatCompletion(id='chatcmpl-9MywRtYSqfA8Bpn45HOzRNinjBSSX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal issue", "funds access problem", "unable to withdraw"]', role='assistant', function_call=None, tool_calls=None))], created=1715264503, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["withdrawal issue", "funds access problem", "unable to withdraw"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need your help to check my account, please! My card keeps being declined at the ATM, and I've already tried two different ones!"

Keyphrases:
1570it [54:35,  1.71s/it]
ChatCompletion(id='chatcmpl-9MywS5bVR0jvc0KCBL5thaCdKw8xJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account check", "card declined", "ATM issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264504, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=247, total_tokens=260))
["account check", "card declined", "ATM issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hi, My card withdrawal was declined this morning. It was working fine till yesterday. Please check and inform me."

Keyphrases:
1571it [54:37,  1.60s/it]
ChatCompletion(id='chatcmpl-9MywUQjlUdUI8al6fSSSin7abIkeY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card withdrawal declined", "withdrawal issue", "transaction declined"]', role='assistant', function_call=None, tool_calls=None))], created=1715264506, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=241, total_tokens=255))
["card withdrawal declined", "withdrawal issue", "transaction declined"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hi, I was trying to use my card but it was declining by ATM. I have cross checked with two different ATMs but i was facing the same issue. Could you please check my account."

Keyphrases:
1572it [54:39,  1.73s/it]
ChatCompletion(id='chatcmpl-9MywVsWa1y7YGvAq5M2HHmupGDKhP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "ATM issue", "account problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264507, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=258, total_tokens=271))
["card declined", "ATM issue", "account problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to make a cash withdrawal and it was declined. Why did this happen?"

Keyphrases:
1573it [54:40,  1.58s/it]
ChatCompletion(id='chatcmpl-9MywXiJglZYXxX485x09vTE07bOWW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal declined", "ATM withdrawal issue", "withdrawal problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264509, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=235, total_tokens=251))
["cash withdrawal declined", "ATM withdrawal issue", "withdrawal problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't get money out of the ATM"

Keyphrases:
1574it [54:44,  2.22s/it]
ChatCompletion(id='chatcmpl-9MywYZbSbuqgKwXlT4vtvcU2eGBhC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "withdrawal problem", "unable to withdraw"]', role='assistant', function_call=None, tool_calls=None))], created=1715264510, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["ATM withdrawal issue", "withdrawal problem", "unable to withdraw"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM is declining my card. I tried at two different ATMs. Can you tell me if there's anything wrong with my account?"

Keyphrases:
1575it [54:45,  2.00s/it]
ChatCompletion(id='chatcmpl-9Mywco8KUIGwnMBXYj4s0KCva41xt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card decline", "multiple ATM failures", "account issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715264514, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=246, total_tokens=261))
["ATM card decline", "multiple ATM failures", "account issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The withdrawal was declined I am unsure as to why this happened?"

Keyphrases:
1576it [54:46,  1.75s/it]
ChatCompletion(id='chatcmpl-9MywevJhXSIF3d1KuuAArQDJ4tnpP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal declined", "failed withdrawal", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264516, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["withdrawal declined", "failed withdrawal", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was declined when I tried to get cash."

Keyphrases:
1577it [54:48,  1.82s/it]
ChatCompletion(id='chatcmpl-9MywfprYWtf1TKpNqXadPM3KQgIUs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["declined transaction", "cash withdrawal issue", "ATM decline"]', role='assistant', function_call=None, tool_calls=None))], created=1715264517, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["declined transaction", "cash withdrawal issue", "ATM decline"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I declined at the ATM today when I was trying to make a withdraw?"

Keyphrases:
1578it [54:50,  1.63s/it]
ChatCompletion(id='chatcmpl-9MywhYywZ3sK5cpn3Zu5wjoGPpciX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM decline", "withdrawal issue", "transaction declined"]', role='assistant', function_call=None, tool_calls=None))], created=1715264519, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["ATM decline", "withdrawal issue", "transaction declined"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are some reasons that would cause ATM machines to decline my card? It has happened to me multiple times!"

Keyphrases:
1579it [54:51,  1.65s/it]
ChatCompletion(id='chatcmpl-9MywiDWqOXWyIztp4Og5Skt015KBN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card decline", "card rejection reasons", "ATM issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715264520, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=240, total_tokens=256))
["ATM card decline", "card rejection reasons", "ATM issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did the ATM machine fail to give me a cash withdrawal?"

Keyphrases:
1580it [54:53,  1.60s/it]
ChatCompletion(id='chatcmpl-9MywkQQ4fTmyjIp10cubvLMKBVHc0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM failure", "cash withdrawal issue", "ATM transaction problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264522, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["ATM failure", "cash withdrawal issue", "ATM transaction problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My ATM transaction was unsuccessful."

Keyphrases:
1581it [54:54,  1.60s/it]
ChatCompletion(id='chatcmpl-9MywlkrBVMf3ZLF6Wgn2OyZpI4ZdL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM transaction issue", "unsuccessful transaction", "ATM failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715264523, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=224, total_tokens=240))
["ATM transaction issue", "unsuccessful transaction", "ATM failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I attempted to get cash but was declined."

Keyphrases:
1582it [54:56,  1.62s/it]
ChatCompletion(id='chatcmpl-9Mywn8iJLYn4B45hD9z7Oy5K7Lcuq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal issue", "ATM decline", "transaction declined"]', role='assistant', function_call=None, tool_calls=None))], created=1715264525, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["cash withdrawal issue", "ATM decline", "transaction declined"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to withdraw money but I was declined!"

Keyphrases:
1583it [54:57,  1.54s/it]
ChatCompletion(id='chatcmpl-9MywonTE8Iijhh80dymwnkGZ0OOd1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal issue", "ATM declined", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715264526, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["withdrawal issue", "ATM declined", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How come I can't take money out of the ATM?"

Keyphrases:
1584it [55:00,  1.75s/it]
ChatCompletion(id='chatcmpl-9MywqAEfqjz7KFAesYV4TWFlY6sgc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "withdrawal problem", "ATM access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264528, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["ATM withdrawal issue", "withdrawal problem", "ATM access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM keeps declining my card. I tried at two different ATMs. Can you tell me if there's an issue with my account?"

Keyphrases:
1585it [55:01,  1.57s/it]
ChatCompletion(id='chatcmpl-9MywsbtArd3ptOSsJPojVXOmHJpSR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card decline", "card issue", "account problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264530, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=246, total_tokens=260))
["ATM card decline", "card issue", "account problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was my cash withdrawal declined?"

Keyphrases:
1586it [55:02,  1.59s/it]
ChatCompletion(id='chatcmpl-9Mywuql5bSo2yDOqDSWvYYgm87QeV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal decline", "withdrawal issues", "transaction declined"]', role='assistant', function_call=None, tool_calls=None))], created=1715264532, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["cash withdrawal decline", "withdrawal issues", "transaction declined"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why could I not get cash?"

Keyphrases:
1587it [55:04,  1.57s/it]
ChatCompletion(id='chatcmpl-9MywvqcWB5tgiZfZDJufoxEl05Ksm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal issue", "ATM problem", "withdrawal failed"]', role='assistant', function_call=None, tool_calls=None))], created=1715264533, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["cash withdrawal issue", "ATM problem", "withdrawal failed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "why couldn't I get cash in the ATM?"

Keyphrases:
1588it [55:05,  1.53s/it]
ChatCompletion(id='chatcmpl-9Myww391vunVOZNnsd34VuPIkZXhs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "cash withdrawal problem", "ATM transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715264534, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["ATM withdrawal issue", "cash withdrawal problem", "ATM transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I get cash?"

Keyphrases:
1589it [55:07,  1.57s/it]
ChatCompletion(id='chatcmpl-9MywyY0JRxKsQa0iJa9q1KRJ7Y5qX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal issue", "ATM issue", "unable to withdraw cash"]', role='assistant', function_call=None, tool_calls=None))], created=1715264536, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["cash withdrawal issue", "ATM issue", "unable to withdraw cash"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why didn't the ATM give me my money?"

Keyphrases:
1590it [55:12,  2.47s/it]
ChatCompletion(id='chatcmpl-9MywzdzXyjqTSx8YQ0hvbqdjG5vuj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "withdrawal problem", "money not dispensed"]', role='assistant', function_call=None, tool_calls=None))], created=1715264537, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["ATM issue", "withdrawal problem", "money not dispensed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "i tried to withdraw money from an atm and i was declined on front of my friends. Why did this happen?"

Keyphrases:
1591it [55:13,  2.22s/it]
ChatCompletion(id='chatcmpl-9Myx4o4P5CNyNCiGmyReKMxJ8XF2I', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal failure", "transaction declined", "withdrawal issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715264542, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=241, total_tokens=256))
["ATM withdrawal failure", "transaction declined", "withdrawal issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM isn't giving out any money."

Keyphrases:
1592it [55:15,  2.02s/it]
ChatCompletion(id='chatcmpl-9Myx5RihbEL8UfBwxTpns83JlOQSl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "withdrawal problem", "ATM malfunction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264543, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["ATM issue", "withdrawal problem", "ATM malfunction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I declined getting cash?"

Keyphrases:
1593it [55:16,  1.84s/it]
ChatCompletion(id='chatcmpl-9Myx7Hw7nIb062fyinOxBVbyXwoJA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal issue", "declined transaction", "ATM withdrawal declined"]', role='assistant', function_call=None, tool_calls=None))], created=1715264545, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["cash withdrawal issue", "declined transaction", "ATM withdrawal declined"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I couldn't get cash at the atm"

Keyphrases:
1594it [55:18,  1.69s/it]
ChatCompletion(id='chatcmpl-9Myx8VZz3WTk0NspIsdsWpen9rVId', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "cash not dispensed", "ATM transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715264546, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=18, prompt_tokens=227, total_tokens=245))
["ATM withdrawal issue", "cash not dispensed", "ATM transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Oh my goodness, my card has been declined twice at ATM! I tried two different ATM, but each one declined my card! Can you tell me what's going on with my account?"

Keyphrases:
1595it [55:19,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyxAmCSfOWamyfpOWFDcXUxGgCRR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "ATM issue", "account status"]', role='assistant', function_call=None, tool_calls=None))], created=1715264548, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=256, total_tokens=269))
["card declined", "ATM issue", "account status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why could I not choose cash at the ATM?"

Keyphrases:
1596it [55:22,  2.05s/it]
ChatCompletion(id='chatcmpl-9MyxCbSG8f8odcToElAgF1235HrBT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "cash withdrawal problem", "selecting cash options"]', role='assistant', function_call=None, tool_calls=None))], created=1715264550, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["ATM issue", "cash withdrawal problem", "selecting cash options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My cash withdrawl was declined why?"

Keyphrases:
1597it [55:24,  2.02s/it]
ChatCompletion(id='chatcmpl-9MyxFC36BJI5nERsLtpP20MYTFxEc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal decline", "transaction issue", "declined transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264553, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["withdrawal decline", "transaction issue", "declined transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a reason that the ATM declined my transaction?"

Keyphrases:
1598it [55:25,  1.77s/it]
ChatCompletion(id='chatcmpl-9MyxGKwi1xWLOyAcm6rhy3YlUQDTU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM transaction decline", "transaction rejection", "declined withdrawal"]', role='assistant', function_call=None, tool_calls=None))], created=1715264554, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["ATM transaction decline", "transaction rejection", "declined withdrawal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The cash I tried to draw from the ATM was not approved."

Keyphrases:
1599it [55:27,  1.66s/it]
ChatCompletion(id='chatcmpl-9MyxIg3c6m160vyaZNsaOP73oAF5k', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal issue", "withdrawal not approved", "cash withdrawal problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264556, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["ATM withdrawal issue", "withdrawal not approved", "cash withdrawal problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "atm would not give me cash"

Keyphrases:
1600it [55:29,  1.77s/it]
ChatCompletion(id='chatcmpl-9MyxJ3xTEJUZ6a6283vL75aPVKuyI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "cash withdrawal problem", "ATM didn\'t dispense cash"]', role='assistant', function_call=None, tool_calls=None))], created=1715264557, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=19, prompt_tokens=226, total_tokens=245))
["ATM issue", "cash withdrawal problem", "ATM didn't dispense cash"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card payment is still on hold, why is it so?"

Keyphrases:
1601it [55:30,  1.63s/it]
ChatCompletion(id='chatcmpl-9MyxL1XOtfvNVUA1nvZElppposXZX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment hold", "card payment issue", "payment status"]', role='assistant', function_call=None, tool_calls=None))], created=1715264559, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["payment hold", "card payment issue", "payment status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my payment pending?"

Keyphrases:
1602it [55:32,  1.69s/it]
ChatCompletion(id='chatcmpl-9MyxMj75ByaMqz5I3etEDY6pM0j9E', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "payment status", "delayed payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715264560, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["pending payment", "payment status", "delayed payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card payment is still pending."

Keyphrases:
1603it [55:35,  2.00s/it]
ChatCompletion(id='chatcmpl-9MyxP7YSSkrVy8cVf3vuq7Qe4YRow', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "card payment status", "payment not processed"]', role='assistant', function_call=None, tool_calls=None))], created=1715264563, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["pending payment", "card payment status", "payment not processed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do i finalize a card payment"

Keyphrases:
1604it [55:36,  1.79s/it]
ChatCompletion(id='chatcmpl-9MyxRFywTOPt6nBlRH01SOOaPEsKE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["finalize payment", "card payment completion", "complete transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264565, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["finalize payment", "card payment completion", "complete transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my card payment showing as pending?"

Keyphrases:
1605it [55:37,  1.72s/it]
ChatCompletion(id='chatcmpl-9MyxSqA4LFPIK8cSYvdSqRkPkbfX6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "card payment status", "transaction pending"]', role='assistant', function_call=None, tool_calls=None))], created=1715264566, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["pending payment", "card payment status", "transaction pending"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why has my payment not gone through?"

Keyphrases:
1606it [55:40,  2.02s/it]
ChatCompletion(id='chatcmpl-9MyxUctKJHkvAiMrJeSKoB1aXPSMb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment failure", "unsuccessful payment", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264568, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["payment failure", "unsuccessful payment", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please help me to know the status of my card payment as its pending since a while."

Keyphrases:
1607it [55:41,  1.80s/it]
ChatCompletion(id='chatcmpl-9MyxWxaPSFNMjtvywd7ZNIqd7iPUV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment status", "pending payment", "payment inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715264570, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=236, total_tokens=249))
["card payment status", "pending payment", "payment inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I recently made a payment, and it is showing up in my account as "pending". What does that mean?"

Keyphrases:
1608it [55:45,  2.45s/it]
ChatCompletion(id='chatcmpl-9MyxYQhmQfM2dWFz16R6gIEJVjGq4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment status", "meaning of pending", "payment processing"]', role='assistant', function_call=None, tool_calls=None))], created=1715264572, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=241, total_tokens=255))
["pending payment status", "meaning of pending", "payment processing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What does it mean by pending payment?"

Keyphrases:
1609it [55:48,  2.55s/it]
ChatCompletion(id='chatcmpl-9MyxcGeTiThcdK3olRDblHXYT1GnB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "payment status", "payment clarification"]', role='assistant', function_call=None, tool_calls=None))], created=1715264576, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["pending payment", "payment status", "payment clarification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will my card payment be done pending?"

Keyphrases:
1610it [55:50,  2.22s/it]
ChatCompletion(id='chatcmpl-9Myxfdr1Lm9XUjmHBcXR5Mh2pCVGa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment status", "pending transaction", "payment processing time"]', role='assistant', function_call=None, tool_calls=None))], created=1715264579, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["card payment status", "pending transaction", "payment processing time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made this payment days ago so why hasn't it gone through yet?"

Keyphrases:
1611it [55:52,  2.34s/it]
ChatCompletion(id='chatcmpl-9MyxgO6C1Ymd3sWTuVPAgXi7lOhDf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment status", "delayed payment", "transaction issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715264580, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["payment status", "delayed payment", "transaction issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am seeing pending from the card payment I made."

Keyphrases:
1612it [55:53,  1.98s/it]
ChatCompletion(id='chatcmpl-9Myxjh4T9uRHFRaIHeyqiDNFz96h6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transaction", "payment status", "card payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264583, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["pending transaction", "payment status", "card payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card payment is showing pending."

Keyphrases:
1613it [55:55,  1.95s/it]
ChatCompletion(id='chatcmpl-9MyxkyiFAsPmq8EIFi14cwl1SdmWY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "card payment status", "payment processing"]', role='assistant', function_call=None, tool_calls=None))], created=1715264584, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["pending payment", "card payment status", "payment processing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I bought some stuff this morning but the payment shows as pending"

Keyphrases:
1614it [55:57,  1.89s/it]
ChatCompletion(id='chatcmpl-9Myxmkctm1Xhx93fCoTerSuIqJzol', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "transaction status", "payment not processed"]', role='assistant', function_call=None, tool_calls=None))], created=1715264586, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["pending payment", "transaction status", "payment not processed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am waiting for a payment to go through."

Keyphrases:
1615it [55:58,  1.68s/it]
ChatCompletion(id='chatcmpl-9MyxnF0SO8iap1INnPXOuy0t5WkbV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment processing", "awaiting transaction", "payment delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715264587, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["payment processing", "awaiting transaction", "payment delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does an item I bought show as pending?"

Keyphrases:
1616it [56:00,  1.60s/it]
ChatCompletion(id='chatcmpl-9MyxoJfdAGxUStlgyzi5QW4fr6OET', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transactions", "transaction status", "pending purchase duration"]', role='assistant', function_call=None, tool_calls=None))], created=1715264588, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["pending transactions", "transaction status", "pending purchase duration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is a pending payment?"

Keyphrases:
1617it [56:02,  1.76s/it]
ChatCompletion(id='chatcmpl-9Myxqfh6VGlwoL8o6KWJvUxL04ErE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "payment status", "unprocessed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264590, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["pending payment", "payment status", "unprocessed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to know why my purchases from this morning are still pending."

Keyphrases:
1618it [56:04,  1.87s/it]
ChatCompletion(id='chatcmpl-9Myxsgs5WYw3ivi13hZ3z0Kma97Ys', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transactions", "transaction status", "payment delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715264592, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=233, total_tokens=245))
["pending transactions", "transaction status", "payment delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is there a pending transaction on my card?"

Keyphrases:
1619it [56:05,  1.75s/it]
ChatCompletion(id='chatcmpl-9MyxuddLbnsoIMMSlKBP28FSk97aw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transaction", "transaction status", "card activity"]', role='assistant', function_call=None, tool_calls=None))], created=1715264594, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["pending transaction", "transaction status", "card activity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card payment is pending."

Keyphrases:
1620it [56:07,  1.63s/it]
ChatCompletion(id='chatcmpl-9MyxwXsrxSz9FAM1RkXzQ02FVrsIq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "payment status", "card payment delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715264596, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["pending payment", "payment status", "card payment delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is a payment showing up on my card as pending?"

Keyphrases:
1621it [56:08,  1.61s/it]
ChatCompletion(id='chatcmpl-9Myxx5GzBHniRFYRTwVY0nZlZPiRV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "payment status", "transaction pending"]', role='assistant', function_call=None, tool_calls=None))], created=1715264597, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["pending payment", "payment status", "transaction pending"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a purchase and it says it's pending. What does that mean?"

Keyphrases:
1622it [56:11,  2.04s/it]
ChatCompletion(id='chatcmpl-9MyxzGSUCYfvKBx1fvFdShI0tNF3i', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transaction", "transaction status", "purchase status"]', role='assistant', function_call=None, tool_calls=None))], created=1715264599, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=234, total_tokens=246))
["pending transaction", "transaction status", "purchase status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long do card transactions take to clear?"

Keyphrases:
1623it [56:13,  1.95s/it]
ChatCompletion(id='chatcmpl-9Myy2M7DTUwae4Qw3N2vWsypCMHMp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction time", "card clearing time", "transaction processing duration"]', role='assistant', function_call=None, tool_calls=None))], created=1715264602, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["transaction time", "card clearing time", "transaction processing duration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what does pending mean?"

Keyphrases:
1624it [56:15,  1.85s/it]
ChatCompletion(id='chatcmpl-9Myy3k9mNycAKSWm3PPxFmmQzSi5B', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending status", "meaning of pending", "transaction status"]', role='assistant', function_call=None, tool_calls=None))], created=1715264603, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["pending status", "meaning of pending", "transaction status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long will this card payment stay pending?"

Keyphrases:
1625it [56:17,  2.10s/it]
ChatCompletion(id='chatcmpl-9Myy5b9Vw2yuhexfbFACh3iC6i1DT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment status", "pending transaction duration", "pending card payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715264605, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["payment status", "pending transaction duration", "pending card payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My payment still hasn't processed!"

Keyphrases:
1626it [56:19,  1.96s/it]
ChatCompletion(id='chatcmpl-9Myy84gsBkyOs86NqvI6NCt8GgvVp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment processing", "delayed payment", "transaction status"]', role='assistant', function_call=None, tool_calls=None))], created=1715264608, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["payment processing", "delayed payment", "transaction status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was double charged, and the second charge is showing as "pending". How long will it be before I get my money back once the second charge has been refunded?"

Keyphrases:
1627it [56:20,  1.77s/it]
ChatCompletion(id='chatcmpl-9Myy9jDyf7W75xFOnTcJttuBFNIwa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "pending refund", "refund timeline"]', role='assistant', function_call=None, tool_calls=None))], created=1715264609, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=252, total_tokens=264))
["double charge", "pending refund", "refund timeline"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have waited 15 days, but my payment still hasn't cleared."

Keyphrases:
1628it [56:21,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyyBvuyzsKMhe8GF5VJmmBohzpfI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment delay", "uncleared payment", "payment processing time"]', role='assistant', function_call=None, tool_calls=None))], created=1715264611, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["payment delay", "uncleared payment", "payment processing time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why would I have a pending payment?"

Keyphrases:
1629it [56:25,  2.05s/it]
ChatCompletion(id='chatcmpl-9MyyD65FG3Us6DsEvzclckP3lPZmI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "payment status", "delayed payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715264613, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["pending payment", "payment status", "delayed payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Explain what the pending payment means?"

Keyphrases:
1630it [56:26,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyyFdOIgKvC2PuO3c38q4XYNbJsS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "payment status", "uncleared payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715264615, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["pending payment", "payment status", "uncleared payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why are my payments showing pending?"

Keyphrases:
1631it [56:28,  1.98s/it]
ChatCompletion(id='chatcmpl-9MyyGTa7AuQxzWCBXdow7PqP7ISqp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payments", "payment status", "transaction delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715264616, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["pending payments", "payment status", "transaction delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is still pending, I've been waiting a while."

Keyphrases:
1632it [56:30,  1.87s/it]
ChatCompletion(id='chatcmpl-9MyyIHMSuXPuJBAZ70NxhMtayt9Cg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending card status", "card processing delay", "wait time for card"]', role='assistant', function_call=None, tool_calls=None))], created=1715264618, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["pending card status", "card processing delay", "wait time for card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does it take for a payment to go thru? I made one a few days ago and it has not been cleared yet."

Keyphrases:
1633it [56:31,  1.82s/it]
ChatCompletion(id='chatcmpl-9MyyKHlmsQT4LrY5QSMu0rJGKLBWS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment processing time", "uncleared payment", "payment status"]', role='assistant', function_call=None, tool_calls=None))], created=1715264620, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=245, total_tokens=259))
["payment processing time", "uncleared payment", "payment status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I bought some things this morning but the payment shows that it is pending"

Keyphrases:
1634it [56:33,  1.81s/it]
ChatCompletion(id='chatcmpl-9MyyMTaj27g8X38SOZebC9sGzXk6s', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "payment status", "transaction pending"]', role='assistant', function_call=None, tool_calls=None))], created=1715264622, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=233, total_tokens=245))
["pending payment", "payment status", "transaction pending"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does it take to authorise a payment?"

Keyphrases:
1635it [56:35,  1.84s/it]
ChatCompletion(id='chatcmpl-9MyyOWrOFI8QTzcNScU4kfBwaeJjz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment authorization", "authorization time", "payment processing time"]', role='assistant', function_call=None, tool_calls=None))], created=1715264624, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["payment authorization", "authorization time", "payment processing time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I had a payment that I made and it's been some amount of time and would like to know when it's suppose to go though."

Keyphrases:
1636it [56:36,  1.69s/it]
ChatCompletion(id='chatcmpl-9MyyPoh0Pzy4oufT2TZPogfHYLsIu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment status", "payment processing time", "transaction completion"]', role='assistant', function_call=None, tool_calls=None))], created=1715264625, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=246, total_tokens=259))
["payment status", "payment processing time", "transaction completion"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What does a pending transaction mean?"

Keyphrases:
1637it [56:40,  2.19s/it]
ChatCompletion(id='chatcmpl-9MyyRpDUEu7yKqYGykHGhCfWU7oVo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transaction explanation", "transaction status", "meaning of pending"]', role='assistant', function_call=None, tool_calls=None))], created=1715264627, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["pending transaction explanation", "transaction status", "meaning of pending"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have paid by my card but payment is still its coming as pending. I think there is some issue please check and let me know when the status will complete."

Keyphrases:
1638it [56:42,  2.06s/it]
ChatCompletion(id='chatcmpl-9MyyUaRaoVpxnsaxyoAKKAYlwYUPI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "payment status", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264630, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=251, total_tokens=263))
["pending payment", "payment status", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a pending payment in my account that I paid a while back ago and it still hasnt gone through. Why would it show pending for so long?"

Keyphrases:
1639it [56:43,  1.85s/it]
ChatCompletion(id='chatcmpl-9MyyWJQxvBWoXGib8G39tpHQcPRM8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "payment status", "delayed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264632, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=250, total_tokens=263))
["pending payment", "payment status", "delayed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a pending payment from stuff I bought this morning."

Keyphrases:
1640it [56:44,  1.70s/it]
ChatCompletion(id='chatcmpl-9MyyXPBQQ0K62FIJ98AtwtDvoiG7p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "payment status", "transaction status"]', role='assistant', function_call=None, tool_calls=None))], created=1715264633, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["pending payment", "payment status", "transaction status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My phone was stolen"

Keyphrases:
1641it [56:46,  1.57s/it]
ChatCompletion(id='chatcmpl-9MyyZdY3Wg19kcpqCtz9ZDqOw6cjb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen phone", "report theft", "lost device"]', role='assistant', function_call=None, tool_calls=None))], created=1715264635, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["stolen phone", "report theft", "lost device"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My phone was stolen yesterday.  What should I do?"

Keyphrases:
1642it [56:47,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyyavrMjCM0xW8EDLcGBcDQZXHIw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen phone", "lost device", "security measures"]', role='assistant', function_call=None, tool_calls=None))], created=1715264636, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["stolen phone", "lost device", "security measures"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If my phone is missing, can I block someone from using the app?"

Keyphrases:
1643it [56:48,  1.40s/it]
ChatCompletion(id='chatcmpl-9MyybYc1QO7kigmxgWncNUvbP0TDg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["block app access", "lost phone", "prevent unauthorized access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264637, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["block app access", "lost phone", "prevent unauthorized access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think my phone is either lost or stolen."

Keyphrases:
1644it [56:50,  1.53s/it]
ChatCompletion(id='chatcmpl-9MyycXf9sa6YU0SGLMep2IOyeV6mv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost phone", "stolen phone", "device security"]', role='assistant', function_call=None, tool_calls=None))], created=1715264638, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["lost phone", "stolen phone", "device security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I was mugged and lost everything, how do I access my account and app?"

Keyphrases:
1645it [56:51,  1.47s/it]
ChatCompletion(id='chatcmpl-9MyyesvtR7yYqZGA9lV3tHG097MaE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account recovery", "lost card", "emergency access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264640, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=236, total_tokens=248))
["account recovery", "lost card", "emergency access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't find my phone."

Keyphrases:
1646it [56:53,  1.52s/it]
ChatCompletion(id='chatcmpl-9MyygUMlpMAYzRu82pkttuVXrxR0M', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost phone", "missing phone", "phone location"]', role='assistant', function_call=None, tool_calls=None))], created=1715264642, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["lost phone", "missing phone", "phone location"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've lost track of my phone or someone stole it."

Keyphrases:
1647it [56:55,  1.56s/it]
ChatCompletion(id='chatcmpl-9Myyht3pnMu0eAiVl7nIIbF8h6OIG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost phone", "phone stolen", "device security"]', role='assistant', function_call=None, tool_calls=None))], created=1715264643, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["lost phone", "phone stolen", "device security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm not sure where my phone is, I think someone stole it or it's lost."

Keyphrases:
1648it [56:58,  2.24s/it]
ChatCompletion(id='chatcmpl-9Myyj4BoCPeYlFjCjt14jDZ9NsBI6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost phone", "stolen phone", "phone location"]', role='assistant', function_call=None, tool_calls=None))], created=1715264645, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=237, total_tokens=250))
["lost phone", "stolen phone", "phone location"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I used my card even if my phone has been stolen?"

Keyphrases:
1649it [57:02,  2.63s/it]
ChatCompletion(id='chatcmpl-9MyynpEtNzEkUFvfAgpCot72hrjtC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card use without phone", "stolen phone card usage", "using card after phone theft"]', role='assistant', function_call=None, tool_calls=None))], created=1715264649, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=20, prompt_tokens=231, total_tokens=251))
["card use without phone", "stolen phone card usage", "using card after phone theft"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My phone was stolen, what do I do?"

Keyphrases:
1650it [57:03,  2.30s/it]
ChatCompletion(id='chatcmpl-9MyyqIZ0Uvw2n9W4lTf3uMRxCm3gm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen phone", "fraud prevention", "block account"]', role='assistant', function_call=None, tool_calls=None))], created=1715264652, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["stolen phone", "fraud prevention", "block account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "lost my phone, dont want others to use it."

Keyphrases:
1651it [57:05,  2.01s/it]
ChatCompletion(id='chatcmpl-9MyysMGWwTHvv58jU7e3KcpUmgWW4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["phone security", "lost phone", "block access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264654, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["phone security", "lost phone", "block access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I lost my phone and need help securing it."

Keyphrases:
1652it [57:07,  2.11s/it]
ChatCompletion(id='chatcmpl-9MyytGOVh3LkYat3POET1ItsTpWVp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost phone", "account security", "secure account"]', role='assistant', function_call=None, tool_calls=None))], created=1715264655, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["lost phone", "account security", "secure account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My phone was stolen so I no longer have access to the app."

Keyphrases:
1653it [57:08,  1.85s/it]
ChatCompletion(id='chatcmpl-9MyyvtK7STmRobiQv1tzMfkMv1yr5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost phone", "app access", "recover account"]', role='assistant', function_call=None, tool_calls=None))], created=1715264657, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["lost phone", "app access", "recover account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "left phone at hotel, how to access app"

Keyphrases:
1654it [57:12,  2.37s/it]
ChatCompletion(id='chatcmpl-9MyyxjlACjI6LeaWvf8pm1JlKu0SG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost phone access", "mobile app access without phone", "app login from new device"]', role='assistant', function_call=None, tool_calls=None))], created=1715264659, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=19, prompt_tokens=228, total_tokens=247))
["lost phone access", "mobile app access without phone", "app login from new device"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My phone is not on me.  How can I use the app?"

Keyphrases:
1655it [57:14,  2.31s/it]
ChatCompletion(id='chatcmpl-9Myz0O0J6x8ztcOAFJ0mAoI9dPRZa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["app access without phone", "alternative login methods", "access without device"]', role='assistant', function_call=None, tool_calls=None))], created=1715264662, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["app access without phone", "alternative login methods", "access without device"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "my phone is gone"

Keyphrases:
1656it [57:15,  2.02s/it]
ChatCompletion(id='chatcmpl-9Myz2SumBKpcKye2MtSArKEuWf88u', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost phone", "phone replacement", "block account access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264664, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["lost phone", "phone replacement", "block account access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My phone is not with me at the moment so I will not be able to access the app."

Keyphrases:
1657it [57:17,  1.81s/it]
ChatCompletion(id='chatcmpl-9Myz41AUCDfjfuA92QA5NoPf18s6w', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["no access to app", "phone unavailable", "app access issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715264666, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=238, total_tokens=253))
["no access to app", "phone unavailable", "app access issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "my phone was taken! can you place cancel my account so no one uses it"

Keyphrases:
1658it [57:18,  1.69s/it]
ChatCompletion(id='chatcmpl-9Myz5qCozxBoj3NcLhaoNYHqWh0xD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account security", "emergency block", "stolen phone"]', role='assistant', function_call=None, tool_calls=None))], created=1715264667, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=235, total_tokens=248))
["account security", "emergency block", "stolen phone"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I lost my phone and would like to freeze my accounts."

Keyphrases:
1659it [57:20,  1.62s/it]
ChatCompletion(id='chatcmpl-9Myz7kveTyuTpAAycqMihJDZooa3N', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account freeze", "lost phone", "emergency freeze"]', role='assistant', function_call=None, tool_calls=None))], created=1715264669, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["account freeze", "lost phone", "emergency freeze"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "lost phone, can i still access account?"

Keyphrases:
1660it [57:22,  1.71s/it]
ChatCompletion(id='chatcmpl-9Myz8hbiWjpEE6QcHg9m1n0tfsneS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost phone", "account access without phone", "mobile banking access issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264670, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["lost phone", "account access without phone", "mobile banking access issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The hotel called and said I left my phone in the room."

Keyphrases:
1661it [57:23,  1.61s/it]
ChatCompletion(id='chatcmpl-9MyzARKrt7m5NboqMY4ETOIslT8Hb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost item", "hotel issue", "left behind item"]', role='assistant', function_call=None, tool_calls=None))], created=1715264672, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["lost item", "hotel issue", "left behind item"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone stole my phone yesterday :( is there anything I need to do?"

Keyphrases:
1662it [57:26,  1.96s/it]
ChatCompletion(id='chatcmpl-9MyzB5BAalpUxLGeWhs3nAjUxAiyA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen phone", "security measure", "report theft"]', role='assistant', function_call=None, tool_calls=None))], created=1715264673, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["stolen phone", "security measure", "report theft"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "lost phone, dont want others to access account"

Keyphrases:
1663it [57:27,  1.76s/it]
ChatCompletion(id='chatcmpl-9MyzEOj1EpyiSB05xunPEtqvDxcWu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["secure account", "lost phone", "prevent unauthorized access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264676, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["secure account", "lost phone", "prevent unauthorized access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was mugged and everything taken.  What do I do to protect my account?"

Keyphrases:
1664it [57:32,  2.64s/it]
ChatCompletion(id='chatcmpl-9MyzFdmP8GeJXRzWqj2vmd0I2QLBj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account security", "emergency block", "theft response"]', role='assistant', function_call=None, tool_calls=None))], created=1715264677, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=236, total_tokens=249))
["account security", "emergency block", "theft response"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I believe I left my smartphone at the hotel I was staying at."

Keyphrases:
1665it [57:33,  2.38s/it]
ChatCompletion(id='chatcmpl-9MyzK0Sb15QBHENcoGdb5wmDVS4BZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost item", "item recovery", "lost smartphone at hotel"]', role='assistant', function_call=None, tool_calls=None))], created=1715264682, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["lost item", "item recovery", "lost smartphone at hotel"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone attacked me yesterday and took my things, so I am unable to use the app.  I am in need of some help."

Keyphrases:
1666it [57:37,  2.62s/it]
ChatCompletion(id='chatcmpl-9MyzMvIS0u8zdu5JTC58hD4krVyvY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["emergency support", "robbery report", "app access issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264684, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=245, total_tokens=259))
["emergency support", "robbery report", "app access issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I still use the app if I switched phones?"

Keyphrases:
1667it [57:39,  2.58s/it]
ChatCompletion(id='chatcmpl-9MyzQAqtFD1Qg9pN8LTvVAKgF5oZm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["app compatibility", "switch devices", "use app on new phone"]', role='assistant', function_call=None, tool_calls=None))], created=1715264688, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["app compatibility", "switch devices", "use app on new phone"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was mugged yesterday and they took everything.  I can't access my app.  What are my next steps?"

Keyphrases:
1668it [57:42,  2.71s/it]
ChatCompletion(id='chatcmpl-9MyzRRTSO3WwA5MK7AuXbXIuRqda8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost card", "emergency support", "theft report", "app access recovery"]', role='assistant', function_call=None, tool_calls=None))], created=1715264689, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=243, total_tokens=261))
["lost card", "emergency support", "theft report", "app access recovery"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got mugged yesterday and lost access to the app. I need to regain it."

Keyphrases:
1669it [57:44,  2.50s/it]
ChatCompletion(id='chatcmpl-9MyzUdb7yMy56w6EWH1WT4rrjMBsq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost access", "account recovery", "emergency support"]', role='assistant', function_call=None, tool_calls=None))], created=1715264692, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=236, total_tokens=248))
["lost access", "account recovery", "emergency support"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I lost my phone, can someone use my account?"

Keyphrases:
1670it [57:46,  2.34s/it]
ChatCompletion(id='chatcmpl-9MyzWKoyIKxCrXzWyAV7ir0Vw5Jox', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account security", "lost phone", "unauthorized access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264694, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["account security", "lost phone", "unauthorized access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am not able to use the app since I forgot my phone at the hotel I was staying at."

Keyphrases:
1671it [57:50,  2.67s/it]
ChatCompletion(id='chatcmpl-9MyzYOovczzXq275W3sjU7a5WetJ6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["app access issue", "lost phone", "unable to use app"]', role='assistant', function_call=None, tool_calls=None))], created=1715264696, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=239, total_tokens=254))
["app access issue", "lost phone", "unable to use app"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone stole my phone."

Keyphrases:
1672it [57:51,  2.24s/it]
ChatCompletion(id='chatcmpl-9MyzcIUAxhVmgsAQGWYSxQaHBHhKS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen phone", "report theft", "security issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264700, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["stolen phone", "report theft", "security issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone stole my cards!"

Keyphrases:
1673it [57:52,  2.00s/it]
ChatCompletion(id='chatcmpl-9MyzdrIgS56HOGdOLnO3d27MxeK7N', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen card", "report theft", "card security"]', role='assistant', function_call=None, tool_calls=None))], created=1715264701, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["stolen card", "report theft", "card security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My phone is lost.  What do I do to prevent someone from using the app?"

Keyphrases:
1674it [57:54,  1.88s/it]
ChatCompletion(id='chatcmpl-9MyzeEDlDLDm9xgDJBZk347Jr3mr5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost phone", "secure account", "prevent unauthorized access"]', role='assistant', function_call=None, tool_calls=None))], created=1715264702, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=236, total_tokens=249))
["lost phone", "secure account", "prevent unauthorized access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there anything I need to do since my phone was stolen?"

Keyphrases:
1675it [57:57,  2.20s/it]
ChatCompletion(id='chatcmpl-9MyzhppwMBwQBzIVqDQZG3LEOkS3U', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen phone actions", "secure account", "report stolen phone"]', role='assistant', function_call=None, tool_calls=None))], created=1715264705, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["stolen phone actions", "secure account", "report stolen phone"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I lost my phone!"

Keyphrases:
1676it [58:01,  2.71s/it]
ChatCompletion(id='chatcmpl-9Myzjc3evVrqjNvQH1NJx0RazvhWA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost phone", "report lost phone", "phone security"]', role='assistant', function_call=None, tool_calls=None))], created=1715264707, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["lost phone", "report lost phone", "phone security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't find my phone but it has all my credit card information."

Keyphrases:
1677it [58:03,  2.54s/it]
ChatCompletion(id='chatcmpl-9MyznNgglbcY2rAzV4HOtG2pLwin8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost phone", "phone security", "credit card information security"]', role='assistant', function_call=None, tool_calls=None))], created=1715264711, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["lost phone", "phone security", "credit card information security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I use the app if I don't have my phone with me?"

Keyphrases:
1678it [58:05,  2.37s/it]
ChatCompletion(id='chatcmpl-9Myzpnj1vm7B4DxdZG3m7jilqD7Ty', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["app access", "alternate login methods", "using app without phone"]', role='assistant', function_call=None, tool_calls=None))], created=1715264713, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["app access", "alternate login methods", "using app without phone"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got mugged yesterday and can't use the app."

Keyphrases:
1679it [58:07,  2.22s/it]
ChatCompletion(id='chatcmpl-9MyzrAUUBkPGSFlWzxKl8DudeJhoX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["theft report", "app access issue", "emergency support"]', role='assistant', function_call=None, tool_calls=None))], created=1715264715, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["theft report", "app access issue", "emergency support"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My things were stolen yesterday and I can't use any apps or anything, so I am going to need some help."

Keyphrases:
1680it [58:08,  2.07s/it]
ChatCompletion(id='chatcmpl-9MyztxNePb2C3TkR0bEhsgyALHGPw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["theft report", "emergency support", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715264717, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=242, total_tokens=255))
["theft report", "emergency support", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hello- It is urgent I get a refund on this product. The merchant has not been helpful, what can I do now to get this resolved ASAP?"

Keyphrases:
1681it [58:10,  1.96s/it]
ChatCompletion(id='chatcmpl-9Myzv8uS9ksiDUmts84qPN5gjSDFz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["urgent refund request", "merchant dispute", "product refund assistance"]', role='assistant', function_call=None, tool_calls=None))], created=1715264719, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=249, total_tokens=263))
["urgent refund request", "merchant dispute", "product refund assistance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I receive a refund for my item?"

Keyphrases:
1682it [58:12,  1.83s/it]
ChatCompletion(id='chatcmpl-9Myzwd7SetfExH4bhZxi44XpHD0iP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund request", "item refund", "request refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264720, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["refund request", "item refund", "request refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Get an item refund"

Keyphrases:
1683it [58:13,  1.76s/it]
ChatCompletion(id='chatcmpl-9Myzy7fQJID1AUa56uGqqSPC7mZrE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["item refund", "refund request", "process refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264722, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["item refund", "refund request", "process refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Would I be able to get a refund for something I bought?"

Keyphrases:
1684it [58:15,  1.77s/it]
ChatCompletion(id='chatcmpl-9Myzz617DgLkGWj4vEFNKglrXlRHB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund request", "purchase refund", "transaction reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715264723, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["refund request", "purchase refund", "transaction reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to do a refund"

Keyphrases:
1685it [58:16,  1.68s/it]
ChatCompletion(id='chatcmpl-9Mz01rYQ6mDmpJ7rCOHoSTrp1CXwg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request refund", "process refund", "initiate refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264725, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["request refund", "process refund", "initiate refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need a refund on an item I have not received.  Am I able to simply cancel the payment?  I don't know how to do this."

Keyphrases:
1686it [58:18,  1.53s/it]
ChatCompletion(id='chatcmpl-9Mz03BVSOSrCOecWNyD1gAJOYQMc4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund request", "cancel payment", "item not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715264727, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=250, total_tokens=263))
["refund request", "cancel payment", "item not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like a refund for something I bought"

Keyphrases:
1687it [58:20,  1.80s/it]
ChatCompletion(id='chatcmpl-9Mz05LqnWLp3dhubcl78gzVr1Ian5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request refund", "purchase refund", "transaction reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715264729, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["request refund", "purchase refund", "transaction reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to return an item."

Keyphrases:
1688it [58:21,  1.65s/it]
ChatCompletion(id='chatcmpl-9Mz06hRPWh1TfWk6uxPN277Daqd4R', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["return item", "item refund", "product return"]', role='assistant', function_call=None, tool_calls=None))], created=1715264730, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["return item", "item refund", "product return"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I have a refund?"

Keyphrases:
1689it [58:22,  1.48s/it]
ChatCompletion(id='chatcmpl-9Mz08X5YIZ9FC6RqjMBlgrXpghXvD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund request", "money back", "process refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264732, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["refund request", "money back", "process refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I wasn't charged the correct amount for an item I purchased, how can I fix this?"

Keyphrases:
1690it [58:25,  1.67s/it]
ChatCompletion(id='chatcmpl-9Mz09PWBMnAz7Ht9U4vi8tJK9bWtz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect charge", "billing issue", "charge dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715264733, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=237, total_tokens=249))
["incorrect charge", "billing issue", "charge dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hi there! I need to cancel an order I recently made and start processing a refund. Can you please help me with this and set up the refund as soon as possible? It's very urgent."

Keyphrases:
1691it [58:26,  1.59s/it]
ChatCompletion(id='chatcmpl-9Mz0B6SVMrKLH1OUyiAUX93KJ4nqA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel order", "process refund", "urgent assistance"]', role='assistant', function_call=None, tool_calls=None))], created=1715264735, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=258, total_tokens=270))
["cancel order", "process refund", "urgent assistance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please stop my purchase."

Keyphrases:
1692it [58:29,  1.89s/it]
ChatCompletion(id='chatcmpl-9Mz0CvN9xaFsGtBLN5CjUobPuRrby', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stop transaction", "halt purchase", "purchase cancellation"]', role='assistant', function_call=None, tool_calls=None))], created=1715264736, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["stop transaction", "halt purchase", "purchase cancellation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want a refund because my package has been taking too long to arrive. How do I go about doing that?"

Keyphrases:
1693it [58:30,  1.73s/it]
ChatCompletion(id='chatcmpl-9Mz0FU8PmiElH9UG0KVvsGOZPlbXO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request refund", "delayed package", "refund process"]', role='assistant', function_call=None, tool_calls=None))], created=1715264739, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=241, total_tokens=254))
["request refund", "delayed package", "refund process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I apply for a refund?"

Keyphrases:
1694it [58:31,  1.56s/it]
ChatCompletion(id='chatcmpl-9Mz0GOZTd6X21yhgNasMo4dAfLWyP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request refund", "apply for refund", "refund process"]', role='assistant', function_call=None, tool_calls=None))], created=1715264740, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["request refund", "apply for refund", "refund process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I have an item refunded?"

Keyphrases:
1695it [58:35,  2.31s/it]
ChatCompletion(id='chatcmpl-9Mz0HDfswJobRjJNQE0tM7Ifs5vrc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["item refund", "refund request", "product refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264741, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["item refund", "refund request", "product refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I ordered something ages ago online but it's simply not arriving. I've got enough! Give me back my money, I'm not paying these people."

Keyphrases:
1696it [58:37,  2.20s/it]
ChatCompletion(id='chatcmpl-9Mz0LLRuAQwdvKpteLTiWo1nFWYNc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund request", "cancel order", "non-receipt of goods"]', role='assistant', function_call=None, tool_calls=None))], created=1715264745, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=249, total_tokens=264))
["refund request", "cancel order", "non-receipt of goods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I need to do to get a refund?"

Keyphrases:
1697it [58:39,  2.16s/it]
ChatCompletion(id='chatcmpl-9Mz0N3bXRnExqnyeKakRHupvfVMij', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund process", "how to get a refund", "refund requirements"]', role='assistant', function_call=None, tool_calls=None))], created=1715264747, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["refund process", "how to get a refund", "refund requirements"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need a refund?"

Keyphrases:
1698it [58:43,  2.62s/it]
ChatCompletion(id='chatcmpl-9Mz0PBrbcJ38Hsc6WMpJFvYaHysmf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund request", "request refund", "processing refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264749, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["refund request", "request refund", "processing refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am unhappy with my purchase, how do I cancel the order?"

Keyphrases:
1699it [58:44,  2.20s/it]
ChatCompletion(id='chatcmpl-9Mz0Tbk17txvpqlt1pZkpDHnbKTcC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel order", "order dissatisfaction", "refund request"]', role='assistant', function_call=None, tool_calls=None))], created=1715264753, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["cancel order", "order dissatisfaction", "refund request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I bought something but now I would like a refund. How do I do that?"

Keyphrases:
1700it [58:45,  1.94s/it]
ChatCompletion(id='chatcmpl-9Mz0UszKuVj5tSZMQJxUMtRc1LHbe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund request", "purchase cancellation", "request refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264754, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=235, total_tokens=247))
["refund request", "purchase cancellation", "request refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I get refunded?"

Keyphrases:
1701it [58:47,  1.86s/it]
ChatCompletion(id='chatcmpl-9Mz0We3cc8uYcfjiOtwfJKv7WtXVw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund process", "request refund", "how to get refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264756, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["refund process", "request refund", "how to get refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you cancel my purchase?"

Keyphrases:
1702it [58:51,  2.37s/it]
ChatCompletion(id='chatcmpl-9Mz0X5RH9NceVjQu8WYzyxebn3E8v', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel purchase", "transaction reversal", "stop payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715264757, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["cancel purchase", "transaction reversal", "stop payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I cancel a previous purchase"

Keyphrases:
1703it [58:52,  2.03s/it]
ChatCompletion(id='chatcmpl-9Mz0b2mfU0ygnPFHcqT3Q9kKYI2mX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel purchase", "reverse transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264761, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=8, prompt_tokens=226, total_tokens=234))
["cancel purchase", "reverse transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would appreciate it if I could get an item refunded"

Keyphrases:
1704it [58:53,  1.79s/it]
ChatCompletion(id='chatcmpl-9Mz0cJbTAXQ2qXSXIw7fxAX5k8sJl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["item refund", "request refund", "product refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264762, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["item refund", "request refund", "product refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I claim a refund?"

Keyphrases:
1705it [58:54,  1.65s/it]
ChatCompletion(id='chatcmpl-9Mz0d6Mczn7tfqegsir89KhvQx7pG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund request", "claim refund", "refund process"]', role='assistant', function_call=None, tool_calls=None))], created=1715264763, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["refund request", "claim refund", "refund process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't want the item, I bought it on accident, can I get a refund?"

Keyphrases:
1706it [58:57,  1.90s/it]
ChatCompletion(id='chatcmpl-9Mz0fzNKHyjGgTW6MoRpSxZCiUYcB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["accidental purchase", "request refund", "order cancellation"]', role='assistant', function_call=None, tool_calls=None))], created=1715264765, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=237, total_tokens=250))
["accidental purchase", "request refund", "order cancellation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hello I changed my mind and really need a refund on one of things I bought recently. Can you please cancel the transaction and get my money back. Please it's urgent."

Keyphrases:
1707it [59:01,  2.43s/it]
ChatCompletion(id='chatcmpl-9Mz0hlsUnQZdWAPwN1sUojaGL4Hbv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["urgent refund request", "cancel transaction", "immediate refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264767, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=253, total_tokens=267))
["urgent refund request", "cancel transaction", "immediate refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like a refund on one of your products that has been sold to me"

Keyphrases:
1708it [59:02,  2.13s/it]
ChatCompletion(id='chatcmpl-9Mz0lLU6nwAe9kLnocT0BcjCPqLOY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request refund", "product refund", "refund process"]', role='assistant', function_call=None, tool_calls=None))], created=1715264771, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=235, total_tokens=247))
["request refund", "product refund", "refund process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am not Happy with this product can i get a refund?"

Keyphrases:
1709it [59:05,  2.29s/it]
ChatCompletion(id='chatcmpl-9Mz0mM6i3TDWojwdlKfuMnmC98l7s', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["product dissatisfaction", "refund request", "return policy"]', role='assistant', function_call=None, tool_calls=None))], created=1715264772, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["product dissatisfaction", "refund request", "return policy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want this amount reversed out of my account."

Keyphrases:
1710it [59:06,  2.06s/it]
ChatCompletion(id='chatcmpl-9Mz0p1W31TZlCiTO7IK5yVC7rHdku', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reverse transaction", "transaction dispute", "refund request"]', role='assistant', function_call=None, tool_calls=None))], created=1715264775, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["reverse transaction", "transaction dispute", "refund request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hello! I recently made a purchase and I'm needing to cancel my order and process a refund as soon as possible."

Keyphrases:
1711it [59:07,  1.81s/it]
ChatCompletion(id='chatcmpl-9Mz0qOI2Aqb2y7lXuvsJPOpykneRD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel order", "process refund", "urgent refund request"]', role='assistant', function_call=None, tool_calls=None))], created=1715264776, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=242, total_tokens=255))
["cancel order", "process refund", "urgent refund request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to reverse a purchase. Can I cancel it?"

Keyphrases:
1712it [59:10,  1.96s/it]
ChatCompletion(id='chatcmpl-9Mz0siccwlnJ54LEpetArcFLC43Kr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reverse purchase", "cancel purchase", "purchase reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715264778, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["reverse purchase", "cancel purchase", "purchase reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am chatting about an order from a long while back.  I never got it to this day and am deeply upset by this!  I want all of my money back!  I just can not accept paying for something I never got."

Keyphrases:
1713it [59:11,  1.88s/it]
ChatCompletion(id='chatcmpl-9Mz0uvcwLYgzVfVw8NuDKp2Uc09Zk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["order issue", "refund request", "non-receipt of goods"]', role='assistant', function_call=None, tool_calls=None))], created=1715264780, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=267, total_tokens=282))
["order issue", "refund request", "non-receipt of goods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I bought this item and was charged the wrong amount can I get a refund?"

Keyphrases:
1714it [59:13,  1.71s/it]
ChatCompletion(id='chatcmpl-9Mz0wJptN4a3P2rqLlIt7eP9qlBhV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect charge", "refund request", "pricing error"]', role='assistant', function_call=None, tool_calls=None))], created=1715264782, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=234, total_tokens=246))
["incorrect charge", "refund request", "pricing error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to cancel a payment. I purchased something several days ago and i still have not received it."

Keyphrases:
1715it [59:15,  1.75s/it]
ChatCompletion(id='chatcmpl-9Mz0xXjrsmWkhLdJT8xloZvF4tU6U', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel payment", "product not received", "refund request"]', role='assistant', function_call=None, tool_calls=None))], created=1715264783, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=240, total_tokens=253))
["cancel payment", "product not received", "refund request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What's the refund process?"

Keyphrases:
1716it [59:16,  1.75s/it]
ChatCompletion(id='chatcmpl-9Mz0zg1Us1S3CY743Ee1F1fBruuP2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund procedure", "how to get a refund", "refund steps"]', role='assistant', function_call=None, tool_calls=None))], created=1715264785, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["refund procedure", "how to get a refund", "refund steps"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want a refund for my purchase"

Keyphrases:
1717it [59:18,  1.72s/it]
ChatCompletion(id='chatcmpl-9Mz11gCdQlwilzXeTYvcv6nqIE6NG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund request", "purchase refund", "transaction reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715264787, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["refund request", "purchase refund", "transaction reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I process a refund for something I purchased?"

Keyphrases:
1718it [59:20,  1.69s/it]
ChatCompletion(id='chatcmpl-9Mz13zD4dFhXaEFool9fZ2Tj0NPC4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund process", "initiate refund", "transaction reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715264789, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["refund process", "initiate refund", "transaction reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to get an item refunded"

Keyphrases:
1719it [59:21,  1.59s/it]
ChatCompletion(id='chatcmpl-9Mz14uPyZQ8g4kF20DZb7mbQ6LHRH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["item refund", "refund request", "process refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264790, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["item refund", "refund request", "process refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to cancel a purchase I made."

Keyphrases:
1720it [59:23,  1.71s/it]
ChatCompletion(id='chatcmpl-9Mz158lwoWCnV5eYQ8SSj4SVZhU1y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel purchase", "transaction reversal", "refund request"]', role='assistant', function_call=None, tool_calls=None))], created=1715264791, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["cancel purchase", "transaction reversal", "refund request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to make a transfer and it was declined. Why?"

Keyphrases:
1721it [59:27,  2.53s/it]
ChatCompletion(id='chatcmpl-9Mz17UnLWV3HFCV18hXXpMMW0C0J5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "reason for decline", "failed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264793, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["transfer declined", "reason for decline", "failed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Good morning. I tried to make a purchase with my credit card last night and again this morning. Both times it was declined. Can you investigate?"

Keyphrases:
1722it [59:29,  2.23s/it]
ChatCompletion(id='chatcmpl-9Mz1CezFy4MkFBKpf6AvVELsuCutf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card declined", "transaction declined", "card refusal investigation"]', role='assistant', function_call=None, tool_calls=None))], created=1715264798, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=248, total_tokens=262))
["credit card declined", "transaction declined", "card refusal investigation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am getting continuous failure for all my transfers. I have cross checked each recipient detail again and again and everything is correct."

Keyphrases:
1723it [59:30,  2.02s/it]
ChatCompletion(id='chatcmpl-9Mz1Do3NjdQntdMfwWUhXIG2TsxyI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issues", "failed transactions", "transfer troubleshooting"]', role='assistant', function_call=None, tool_calls=None))], created=1715264799, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=243, total_tokens=255))
["transfer issues", "failed transactions", "transfer troubleshooting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "why was my transfer declined"

Keyphrases:
1724it [59:32,  1.91s/it]
ChatCompletion(id='chatcmpl-9Mz1FVxur4R30KiHFe13fHzQdKiro', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "declined transaction", "transfer issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264801, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["transfer declined", "declined transaction", "transfer issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What would make a decline message show up during a transfer?"

Keyphrases:
1725it [59:34,  1.83s/it]
ChatCompletion(id='chatcmpl-9Mz1Gmj6OtwcXBM33F1eoJ98Ckmbe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["decline reason", "transfer issues", "transaction decline"]', role='assistant', function_call=None, tool_calls=None))], created=1715264802, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["decline reason", "transfer issues", "transaction decline"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do you keep declining my transfers?it was always been working really well so far but when I tried to buy something just now the card got declined . I tried couple of times already  but same thing is happening."

Keyphrases:
1726it [59:35,  1.69s/it]
ChatCompletion(id='chatcmpl-9Mz1IGoPPc6Rggln8XvMcQwWM4Cx0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer decline", "card declined", "transaction issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715264804, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=262, total_tokens=274))
["transfer decline", "card declined", "transaction issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I fix my card, it got declined twice."

Keyphrases:
1727it [59:38,  2.00s/it]
ChatCompletion(id='chatcmpl-9Mz1KIrfl0KZhRyFTaANtg6oD2Fob', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "fix declined card", "card troubleshooting"]', role='assistant', function_call=None, tool_calls=None))], created=1715264806, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["card declined", "fix declined card", "card troubleshooting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did a transfer get declined?"

Keyphrases:
1728it [59:39,  1.80s/it]
ChatCompletion(id='chatcmpl-9Mz1MdVIuXAorUCJ5HL14der2DIdI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["declined transfer", "transfer rejection", "transfer not approved"]', role='assistant', function_call=None, tool_calls=None))], created=1715264808, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["declined transfer", "transfer rejection", "transfer not approved"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfers are being declined. IT has always worked for me but now it's declining my card. I've tried several times."

Keyphrases:
1729it [59:42,  2.07s/it]
ChatCompletion(id='chatcmpl-9Mz1NhNJJs5qA7ZC0Ff8rl8Zb1aDl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issues", "card declined", "problem with transfers"]', role='assistant', function_call=None, tool_calls=None))], created=1715264809, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=244, total_tokens=257))
["transfer issues", "card declined", "problem with transfers"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did my transfer decline"

Keyphrases:
1730it [59:43,  1.93s/it]
ChatCompletion(id='chatcmpl-9Mz1QQy8cadyshHxz1ECM2snwgelf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer decline", "declined transaction", "transfer issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264812, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["transfer decline", "declined transaction", "transfer issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The card got declined twice when I tried to use it to buy something online yesterday."

Keyphrases:
1731it [59:46,  2.11s/it]
ChatCompletion(id='chatcmpl-9Mz1TIxWkHLOsRGykzqs5TjUqRRyq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "transaction issue", "online purchase decline"]', role='assistant', function_call=None, tool_calls=None))], created=1715264815, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=235, total_tokens=248))
["card declined", "transaction issue", "online purchase decline"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If the transfer details have already but reviewed and confirmed that they are correct, what other reason would cause my transfer to be declined?"

Keyphrases:
1732it [59:48,  2.07s/it]
ChatCompletion(id='chatcmpl-9Mz1U8kaHMpRMkV8GOIHjqkGymZJq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "transaction issues", "bank transfer rejection reasons"]', role='assistant', function_call=None, tool_calls=None))], created=1715264816, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=244, total_tokens=258))
["transfer declined", "transaction issues", "bank transfer rejection reasons"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I get a transfer declined?"

Keyphrases:
1733it [59:50,  1.97s/it]
ChatCompletion(id='chatcmpl-9Mz1W3HJBdp3NPnPS9OHRhnnQIlvw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "declined transaction", "transfer issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715264818, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["transfer declined", "declined transaction", "transfer issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did my my transfer get declined?"

Keyphrases:
1734it [59:52,  2.01s/it]
ChatCompletion(id='chatcmpl-9Mz1Yxvm8Ym57im2h5Z584CukYnX0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer decline", "reason for transfer failure", "transfer not processed"]', role='assistant', function_call=None, tool_calls=None))], created=1715264820, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["transfer decline", "reason for transfer failure", "transfer not processed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I contact customer support about a transfer?"

Keyphrases:
1735it [59:54,  1.93s/it]
ChatCompletion(id='chatcmpl-9Mz1aAcrLukt8ROGf63v3i6vSkFjY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["customer support contact", "support for transfer issue", "contact bank support"]', role='assistant', function_call=None, tool_calls=None))], created=1715264822, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["customer support contact", "support for transfer issue", "contact bank support"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "You keep declining my transfers? It's always been working really well so far, but when I tried to buy something just now the card got declined. I tried couple times already but same thing."

Keyphrases:
1736it [59:55,  1.81s/it]
ChatCompletion(id='chatcmpl-9Mz1ceVeXqoNJJJot4h3VwY6P1f4C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["declined transactions", "card issue", "transfer issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264824, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=257, total_tokens=270))
["declined transactions", "card issue", "transfer issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I unable to do a transfer?"

Keyphrases:
1737it [59:57,  1.70s/it]
ChatCompletion(id='chatcmpl-9Mz1dMnqlU12EbakeC4ZfkGBgQ9Wl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "unable to transfer", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715264825, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["transfer issue", "unable to transfer", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Trouble transferring transaction contact for help"

Keyphrases:
1738it [59:58,  1.55s/it]
ChatCompletion(id='chatcmpl-9Mz1fLu0q7dOOfmkPu6G81CTTHkjT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issues", "transaction support", "help with transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715264827, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["transfer issues", "transaction support", "help with transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why could my transfer have been declined?"

Keyphrases:
1739it [59:59,  1.52s/it]
ChatCompletion(id='chatcmpl-9Mz1gL78UNNSnFPAr7gvbEQgjuzta', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "declined transaction", "failed transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715264828, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["transfer declined", "declined transaction", "failed transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When I try and to buy something using my card it keeps getting declined."

Keyphrases:
1740it [1:00:01,  1.48s/it]
ChatCompletion(id='chatcmpl-9Mz1hk8xUclWldGjEUsXYobmhIlBp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "transaction failure", "payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264829, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=233, total_tokens=245))
["card declined", "transaction failure", "payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I could not do a transfer because it was declined"

Keyphrases:
1741it [1:00:02,  1.56s/it]
ChatCompletion(id='chatcmpl-9Mz1j3IzT21eLCqr8x8icGhVOvyth', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "failed transfer", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264831, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["transfer declined", "failed transfer", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When I submit a transfer, it is being declined.  The information I put in has been reviewed."

Keyphrases:
1742it [1:00:04,  1.46s/it]
ChatCompletion(id='chatcmpl-9Mz1lUBZqg11f8vnkdS3JSOxn79Bp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "failed transaction", "reviewed information error"]', role='assistant', function_call=None, tool_calls=None))], created=1715264833, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=239, total_tokens=253))
["transfer declined", "failed transaction", "reviewed information error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was the transfer declined?"

Keyphrases:
1743it [1:00:06,  1.79s/it]
ChatCompletion(id='chatcmpl-9Mz1maRH5Mpjo2Tw0bEAd4Q8lRl8D', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "failed transaction", "declined transfer issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264834, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["transfer declined", "failed transaction", "declined transfer issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the reason my transfer was declined?"

Keyphrases:
1744it [1:00:08,  1.77s/it]
ChatCompletion(id='chatcmpl-9Mz1o8vB8v9YtomufBfwRyi0bF9HN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "reason for transfer failure", "transfer issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264836, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["transfer declined", "reason for transfer failure", "transfer issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer got declined."

Keyphrases:
1745it [1:00:09,  1.72s/it]
ChatCompletion(id='chatcmpl-9Mz1qTqqoYOgvxvXbLHkWQaFJmOys', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "declined transaction", "failure in money transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715264838, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=223, total_tokens=238))
["transfer declined", "declined transaction", "failure in money transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer was declined"

Keyphrases:
1746it [1:00:12,  2.02s/it]
ChatCompletion(id='chatcmpl-9Mz1sW9b23Md5N9SRSYWEC56P24kI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer status", "declined transfer", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264840, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["transfer status", "declined transfer", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tired to move my money, but my transfer was declined."

Keyphrases:
1747it [1:00:14,  1.96s/it]
ChatCompletion(id='chatcmpl-9Mz1vQwmf1VgKPOrP173USkter1NG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "money transfer issue", "failed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264843, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["transfer declined", "money transfer issue", "failed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to know why my transfer was declined."

Keyphrases:
1748it [1:00:16,  2.12s/it]
ChatCompletion(id='chatcmpl-9Mz1wmDN5WP9LuauH5x2KKaWTRGyN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["declined transfer", "transfer issue", "reason for transfer decline"]', role='assistant', function_call=None, tool_calls=None))], created=1715264844, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["declined transfer", "transfer issue", "reason for transfer decline"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to make a transfer, but it was declined. Can you tell me why?"

Keyphrases:
1749it [1:00:18,  2.00s/it]
ChatCompletion(id='chatcmpl-9Mz1zZPy6mRI8ehsiUIQRUrCeGWnV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "reason for decline", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264847, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=236, total_tokens=249))
["transfer declined", "reason for decline", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "For what reason was my transfer declined?"

Keyphrases:
1750it [1:00:20,  1.92s/it]
ChatCompletion(id='chatcmpl-9Mz201FJ16CcErnfipB99fO4gPhWn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "declined transaction", "transfer issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715264848, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["transfer declined", "declined transaction", "transfer issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer has been declined and I know it should have went through."

Keyphrases:
1751it [1:00:21,  1.71s/it]
ChatCompletion(id='chatcmpl-9Mz22aPBbIOu9Sp4uhQNypNZtCQ90', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["declined transfer", "transfer issue", "failed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264850, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["declined transfer", "transfer issue", "failed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Double check your funds may be declined"

Keyphrases:
1752it [1:00:23,  1.63s/it]
ChatCompletion(id='chatcmpl-9Mz23miwf8ZrGSLv9QC8FxfMivR2q', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund status", "declined transaction", "check balance"]', role='assistant', function_call=None, tool_calls=None))], created=1715264851, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["fund status", "declined transaction", "check balance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't transfer money from my account."

Keyphrases:
1753it [1:00:24,  1.56s/it]
ChatCompletion(id='chatcmpl-9Mz251RZ8aZX9SrUNRbx3JFHZbaZS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "money transfer problem", "unable to transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715264853, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["transfer issue", "money transfer problem", "unable to transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why would my transfer be declined? I've checked that I've put in all the right details, but it is still declined."

Keyphrases:
1754it [1:00:26,  1.67s/it]
ChatCompletion(id='chatcmpl-9Mz26Qcav4yIbqGKZ68D6GHsoDUb4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer declined", "failed transaction", "transaction issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715264854, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=244, total_tokens=256))
["transfer declined", "failed transaction", "transaction issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to buy something online yesterday but it kept saying declined. Tried again today but same thing happened. What's broken?"

Keyphrases:
1755it [1:00:29,  2.17s/it]
ChatCompletion(id='chatcmpl-9Mz28idjjkYfK69zViEie7eddAsDU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction declined", "online purchase issue", "payment failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715264856, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=243, total_tokens=256))
["transaction declined", "online purchase issue", "payment failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to buy something online yesterday but it wouldn't stop saying declined. Tried again today but same thing happened. What's Broken?"

Keyphrases:
1756it [1:00:31,  1.92s/it]
ChatCompletion(id='chatcmpl-9Mz2CBFJEnCWJsNXCq4eUuSXUZZoP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment declined", "transaction issue", "online purchase failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715264860, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=245, total_tokens=258))
["payment declined", "transaction issue", "online purchase failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is being declined online. Could you tell me what might be broken or wrong with the account?"

Keyphrases:
1757it [1:00:32,  1.68s/it]
ChatCompletion(id='chatcmpl-9Mz2DDpgtfn9h7gH9mPs0xAouiCdV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "transaction issues", "account problems"]', role='assistant', function_call=None, tool_calls=None))], created=1715264861, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=239, total_tokens=251))
["card declined", "transaction issues", "account problems"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there any restrictions causing my transfer to be declined?"

Keyphrases:
1758it [1:00:33,  1.61s/it]
ChatCompletion(id='chatcmpl-9Mz2EBOBBqz1MyHCpm957rxO8qINA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issues", "declined transfer", "transfer restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715264862, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["transfer issues", "declined transfer", "transfer restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was attempting to purchase a golf club off eBay yesterday, but my credit card was declined. I tried multiple times, and again this morning. Can you check into my card please?"

Keyphrases:
1759it [1:00:34,  1.52s/it]
ChatCompletion(id='chatcmpl-9Mz2FjivXJ0e6cmFx43uyWpCCU19M', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "purchase issue", "credit card problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264863, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=255, total_tokens=268))
["card declined", "purchase issue", "credit card problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think my transfer was declined, but why?"

Keyphrases:
1760it [1:00:36,  1.62s/it]
ChatCompletion(id='chatcmpl-9Mz2HYoJKkzSe2kppZkX13qYJqDxs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["declined transfer", "transfer issue", "reason for declined transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715264865, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["declined transfer", "transfer issue", "reason for declined transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The refund isn't showing up on my account."

Keyphrases:
1761it [1:00:39,  1.99s/it]
ChatCompletion(id='chatcmpl-9Mz2JLWHQy2140kIxpKquu1pB9nwl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing refund", "refund not credited", "account balance issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264867, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["missing refund", "refund not credited", "account balance issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My refund is missing from my statement."

Keyphrases:
1762it [1:00:42,  2.13s/it]
ChatCompletion(id='chatcmpl-9Mz2L4aAbZDVcmzfTPBzuYRyOFtKN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing refund", "refund status", "statement issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264869, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["missing refund", "refund status", "statement issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I requested a refund, and never received it. What can I do?"

Keyphrases:
1763it [1:00:44,  2.18s/it]
ChatCompletion(id='chatcmpl-9Mz2O2S8bvDYgHEp0UgyrNvroaZQ1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "refund not received", "refund issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264872, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["refund status", "refund not received", "refund issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was supposed to get a purchase refunded but I don't see the money in my account"

Keyphrases:
1764it [1:00:45,  1.99s/it]
ChatCompletion(id='chatcmpl-9Mz2QVIRJo5WudJM3OmBjWxgahmXI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund not received", "missing refund", "refund status"]', role='assistant', function_call=None, tool_calls=None))], created=1715264874, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=237, total_tokens=250))
["refund not received", "missing refund", "refund status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There's a refund missing from my statement"

Keyphrases:
1765it [1:00:48,  2.03s/it]
ChatCompletion(id='chatcmpl-9Mz2S9Je3Q1865h50KcMNz8cksGqp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing refund", "refund not shown", "statement discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715264876, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["missing refund", "refund not shown", "statement discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need help. I asked for a refund from a merchant a while ago, but I have not gotten my money back. I keep checking my account, but nothing is showing up. What should I do now?"

Keyphrases:
1766it [1:00:50,  2.01s/it]
ChatCompletion(id='chatcmpl-9Mz2Urodn5gbf0W3X04ruiRPj0ohX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "merchant refund", "refund not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715264878, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=261, total_tokens=274))
["refund status", "merchant refund", "refund not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am awaiting my refund"

Keyphrases:
1767it [1:00:51,  1.82s/it]
ChatCompletion(id='chatcmpl-9Mz2WU1iy4w8y9SE3nG1GIa7UtCFK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["awaiting refund", "refund status", "refund delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715264880, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["awaiting refund", "refund status", "refund delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does it take for a refund?"

Keyphrases:
1768it [1:00:52,  1.71s/it]
ChatCompletion(id='chatcmpl-9Mz2X1zZoxtbX3PJFiJ7FRDBcD71w', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund duration", "refund process time", "time to get refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264881, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["refund duration", "refund process time", "time to get refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help! I keep checking my account, but my refund is not showing. I requested that a seller refund my money a while back, but there is no money showing in my account. What can you do for me?"

Keyphrases:
1769it [1:00:54,  1.63s/it]
ChatCompletion(id='chatcmpl-9Mz2Z01vnQleRrFvbvkL43gTSCsnO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "pending refund", "refund not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715264883, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=262, total_tokens=275))
["refund status", "pending refund", "refund not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me why my refund is not showing in my statement?"

Keyphrases:
1770it [1:00:57,  1.97s/it]
ChatCompletion(id='chatcmpl-9Mz2cgN3bNK5uXwMc7aNkv7Z0oo2w', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "missing refund", "financial statement query"]', role='assistant', function_call=None, tool_calls=None))], created=1715264886, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["refund status", "missing refund", "financial statement query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I asked for a refund last week but nothing has happened yet, can you help me please?"

Keyphrases:
1771it [1:00:58,  1.75s/it]
ChatCompletion(id='chatcmpl-9Mz2d6ww3izaXWwABW1UaN6j3dLeA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "delayed refund", "refund help"]', role='assistant', function_call=None, tool_calls=None))], created=1715264887, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=237, total_tokens=250))
["refund status", "delayed refund", "refund help"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my refund missing from my  statement?"

Keyphrases:
1772it [1:00:59,  1.68s/it]
ChatCompletion(id='chatcmpl-9Mz2eagA2jd7iSSvYxQPysFkdHbCl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing refund", "refund not shown", "statement issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264888, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["missing refund", "refund not shown", "statement issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Still waiting on a refund."

Keyphrases:
1773it [1:01:01,  1.67s/it]
ChatCompletion(id='chatcmpl-9Mz2gojWETzAs18GpPmGzuOZ614Ou', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending refund", "refund status", "delayed refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264890, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["pending refund", "refund status", "delayed refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I requested a refund and it is missing."

Keyphrases:
1774it [1:01:03,  1.78s/it]
ChatCompletion(id='chatcmpl-9Mz2hLn4HXvWCE4uMct1ozAmw828Z', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "missing refund", "refund request tracking"]', role='assistant', function_call=None, tool_calls=None))], created=1715264891, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["refund status", "missing refund", "refund request tracking"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hi, As suggested by you, i have asked the seller to initiate the refund, it has been a week and i haven't received my money. Please advise."

Keyphrases:
1775it [1:01:05,  1.71s/it]
ChatCompletion(id='chatcmpl-9Mz2jHpzLd7BcgtfBSt1plwmYIlEI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "pending refund", "refund delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715264893, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=251, total_tokens=263))
["refund status", "pending refund", "refund delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I bought something and returned it and the money from the return isn't in my account."

Keyphrases:
1776it [1:01:06,  1.66s/it]
ChatCompletion(id='chatcmpl-9Mz2loGlp25Q91KMVKfydHj6GOL9v', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund processing", "return funds missing", "transaction reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715264895, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=236, total_tokens=249))
["refund processing", "return funds missing", "transaction reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you have any idea on when I will receive my refund? I got my statement and it was not there."

Keyphrases:
1777it [1:01:08,  1.59s/it]
ChatCompletion(id='chatcmpl-9Mz2m6ZFNiAQR2RKSKUy416lb5M05', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "missing refund", "refund delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715264896, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=241, total_tokens=253))
["refund status", "missing refund", "refund delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why isn't a recent refund on my statement?"

Keyphrases:
1778it [1:01:09,  1.46s/it]
ChatCompletion(id='chatcmpl-9Mz2o2ByZRn9tbHgv8YrFgQ22TZmy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing refund", "refund not showing", "statement issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264898, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["missing refund", "refund not showing", "statement issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I see the refund in my account"

Keyphrases:
1779it [1:01:11,  1.83s/it]
ChatCompletion(id='chatcmpl-9Mz2pPOZx8phpLJS9yfQNbI1katxE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "view refund", "account refund visibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715264899, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["refund status", "view refund", "account refund visibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "i was supposed to get a refund but my balance hasn't changed, why not?"

Keyphrases:
1780it [1:01:13,  1.75s/it]
ChatCompletion(id='chatcmpl-9Mz2sKj7oN6aGJ6pZQsq4dBObpA6C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "balance inquiry", "pending refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264902, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=235, total_tokens=247))
["refund status", "balance inquiry", "pending refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I requested a refund from a merchant days ago but I do not see it in my account."

Keyphrases:
1781it [1:01:17,  2.35s/it]
ChatCompletion(id='chatcmpl-9Mz2tluTXFsQTzrlbdzvubL8cS1Dr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "merchant refund", "pending refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264903, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=237, total_tokens=249))
["refund status", "merchant refund", "pending refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The refund has not appeared in my account"

Keyphrases:
1782it [1:01:19,  2.41s/it]
ChatCompletion(id='chatcmpl-9Mz2xqTHGQQ8AeteIDshTGbHxb7FH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "missing refund", "refund not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715264907, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["refund status", "missing refund", "refund not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Did my refund go through? It's not on my statement."

Keyphrases:
1783it [1:01:21,  2.19s/it]
ChatCompletion(id='chatcmpl-9Mz30pA6zV6Rjq3wxAifuMpiNUrdZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "transaction update", "missing refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264910, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["refund status", "transaction update", "missing refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My statement doesn't show that a refund has processed"

Keyphrases:
1784it [1:01:22,  1.87s/it]
ChatCompletion(id='chatcmpl-9Mz31nrsxrqnpKcHKXKJeMHb2ANOO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "statement update", "missing refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264911, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["refund status", "statement update", "missing refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I requested a refund from a store but it hasn't arrived."

Keyphrases:
1785it [1:01:23,  1.65s/it]
ChatCompletion(id='chatcmpl-9Mz327G1TDHF9ibF0OQKGegC2DSLV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "delayed refund", "refund not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715264912, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["refund status", "delayed refund", "refund not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I still haven't seen a refund on my account"

Keyphrases:
1786it [1:01:25,  1.63s/it]
ChatCompletion(id='chatcmpl-9Mz33sqwW0CrUN9U20GwnFMB80OiL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "refund delay", "missing refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264913, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["refund status", "refund delay", "missing refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am missing a refund."

Keyphrases:
1787it [1:01:28,  2.22s/it]
ChatCompletion(id='chatcmpl-9Mz35nz1J1UypKQt5ZLGPFNeBp2KP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing refund", "refund not received", "refund status"]', role='assistant', function_call=None, tool_calls=None))], created=1715264915, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["missing refund", "refund not received", "refund status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My refund doesn't seem to be showing on my statement."

Keyphrases:
1788it [1:01:30,  1.96s/it]
ChatCompletion(id='chatcmpl-9Mz39N4YYFvn8QTA1X7M6wehRWN2i', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing refund", "refund not showing", "statement issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264919, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["missing refund", "refund not showing", "statement issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am not seeing a refund in my statement."

Keyphrases:
1789it [1:01:31,  1.75s/it]
ChatCompletion(id='chatcmpl-9Mz3AZw3MlYIrUXT4EEQIBha72EHz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing refund", "refund status", "statement issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264920, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["missing refund", "refund status", "statement issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I see a recent refund in my statement?"

Keyphrases:
1790it [1:01:33,  1.81s/it]
ChatCompletion(id='chatcmpl-9Mz3BGm2TyrOESMtBY7wbblRoAXVT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund visibility", "statement update", "missing refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264921, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["refund visibility", "statement update", "missing refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I did what you told me earlier and contacted the seller for a refund directly, but nothing is happening! It's been a week and I still haven't got anything. Please just give me back my money"

Keyphrases:
1791it [1:01:34,  1.64s/it]
ChatCompletion(id='chatcmpl-9Mz3DQFNP2A2UPYZ7oR4vwzcuhq8o', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund request", "seller dispute", "no response from seller"]', role='assistant', function_call=None, tool_calls=None))], created=1715264923, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=260, total_tokens=274))
["refund request", "seller dispute", "no response from seller"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is my refund? I have been checking my account all day."

Keyphrases:
1792it [1:01:36,  1.58s/it]
ChatCompletion(id='chatcmpl-9Mz3EwFWpeQ9LOxMP6wz8jplEHK9R', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "refund tracking", "missing refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264924, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["refund status", "refund tracking", "missing refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It's been a week and I have done everything that I was asked to do and still nothing. I have contacted the seller and have not gotten a response. Please understand my frustration and put the money back in my account."

Keyphrases:
1793it [1:01:37,  1.52s/it]
ChatCompletion(id='chatcmpl-9Mz3GqjhaVWQIwKxy6HfrWHiaQ64g', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund request", "seller non-responsive", "escalation request"]', role='assistant', function_call=None, tool_calls=None))], created=1715264926, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=263, total_tokens=277))
["refund request", "seller non-responsive", "escalation request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My refund is missing"

Keyphrases:
1794it [1:01:39,  1.62s/it]
ChatCompletion(id='chatcmpl-9Mz3HVf4VZjfdC5I8mA0Z6RiTrjcV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing refund", "refund status", "delayed refund"]', role='assistant', function_call=None, tool_calls=None))], created=1715264927, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["missing refund", "refund status", "delayed refund"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why doesn't a return show up im my account from a purchase I made?"

Keyphrases:
1795it [1:01:44,  2.58s/it]
ChatCompletion(id='chatcmpl-9Mz3J99021QqIw3vtqoDPpkpUhHrA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["return not showing", "missing transaction", "account update delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715264929, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["return not showing", "missing transaction", "account update delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I keep checking my bank statements but I don't see a refund that I've requested from a seller. Can you ensure that I receive the refund from the seller?"

Keyphrases:
1796it [1:01:46,  2.48s/it]
ChatCompletion(id='chatcmpl-9Mz3O7D93OYg1HxeNe2RQ5GoYRBcC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "requested refund", "seller refund issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264934, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=251, total_tokens=264))
["refund status", "requested refund", "seller refund issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am waiting patiently for a week now for the seller to get back to me and there has been no response, could you please help me further with getting my money back.  Thank you."

Keyphrases:
1797it [1:01:48,  2.33s/it]
ChatCompletion(id='chatcmpl-9Mz3QgQ4KeqMdi88LZzFoS7YFR2ns', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["seller response", "refund assistance", "customer support"]', role='assistant', function_call=None, tool_calls=None))], created=1715264936, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=257, total_tokens=269))
["seller response", "refund assistance", "customer support"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like some help getting a refund back from a seller. It still isn't showing up on my statement and I requested this a long time ago. I'm not sure why it's not returned yet. Can you assist me in getting this money back?"

Keyphrases:
1798it [1:01:50,  2.30s/it]
ChatCompletion(id='chatcmpl-9Mz3S9dFMqg3nRyRjSjEZ8cfekqs1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund request", "seller refund assistance", "missing refund", "refund not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715264938, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=270, total_tokens=288))
["refund request", "seller refund assistance", "missing refund", "refund not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long will it take to get my refund"

Keyphrases:
1799it [1:01:51,  1.98s/it]
ChatCompletion(id='chatcmpl-9Mz3UPlenQ2nXbPbPMNUWpC0sdXDG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund timing", "refund process duration", "refund ETA"]', role='assistant', function_call=None, tool_calls=None))], created=1715264940, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["refund timing", "refund process duration", "refund ETA"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I should have received a refund however it is not showing on my statement"

Keyphrases:
1800it [1:01:54,  2.18s/it]
ChatCompletion(id='chatcmpl-9Mz3W5iJKoKqvQUtnlCOKmz21Ccmi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund not received", "missing refund", "statement discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715264942, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["refund not received", "missing refund", "statement discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My credit card was declined."

Keyphrases:
1801it [1:01:56,  2.18s/it]
ChatCompletion(id='chatcmpl-9Mz3Zrrcrl7j8QnyLD0WxHTlxr1b4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card declined", "payment declined", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715264945, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["credit card declined", "payment declined", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The new card that was just sent to me was declined multiple times yesterday when I tried to use it at a restaurant to pay for my dinner.  I am really disappointed  and embarrassed that my card was denied when I tried to use it to pay for my friend's birthday dinner."

Keyphrases:
1802it [1:01:58,  2.12s/it]
ChatCompletion(id='chatcmpl-9Mz3a5XNq3IuFxICL3zNAAP5SYfLN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "transaction denied", "payment failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715264946, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=275, total_tokens=287))
["card declined", "transaction denied", "payment failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was my card payment declined?"

Keyphrases:
1803it [1:02:00,  2.01s/it]
ChatCompletion(id='chatcmpl-9Mz3dLLJSg6lclGsPvFjG6npm8ceM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment declined", "card declined", "transaction rejected"]', role='assistant', function_call=None, tool_calls=None))], created=1715264949, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["payment declined", "card declined", "transaction rejected"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was trying to purchase something at the store today and my card has been declined.  Why has this happened?"

Keyphrases:
1804it [1:02:02,  1.88s/it]
ChatCompletion(id='chatcmpl-9Mz3ffhFt2dF2jN3N7OvPG3SNLcPP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "purchase declined", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715264951, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=241, total_tokens=253))
["card declined", "purchase declined", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My payment has been declined, I thought this issue was fixed!"

Keyphrases:
1805it [1:02:03,  1.90s/it]
ChatCompletion(id='chatcmpl-9Mz3gmag8f7dj33u0pSEPsw3wlBze', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment declined", "issue resolution", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264952, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["payment declined", "issue resolution", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card was declined in a shop"

Keyphrases:
1806it [1:02:05,  1.70s/it]
ChatCompletion(id='chatcmpl-9Mz3iqaz9aC9AoPOkOR3Bhuc67qct', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "transaction refusal", "payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264954, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["card declined", "transaction refusal", "payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did it decline my payment?"

Keyphrases:
1807it [1:02:07,  1.99s/it]
ChatCompletion(id='chatcmpl-9Mz3jOPDtoRMUcu9hVNC7mpmtnURf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment decline", "declined transaction", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264955, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["payment decline", "declined transaction", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card declined"

Keyphrases:
1808it [1:02:09,  1.83s/it]
ChatCompletion(id='chatcmpl-9Mz3mVOt0UeFSrG78wzwRMREueKpq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "transaction failure", "declined payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715264958, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=222, total_tokens=235))
["card declined", "transaction failure", "declined payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you look at my account ans see why my card was declined"

Keyphrases:
1809it [1:02:10,  1.73s/it]
ChatCompletion(id='chatcmpl-9Mz3nn16His76EBwbCKTA8kfYhFDE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "account review", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264959, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["card declined", "account review", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was out today looking forward to pay with my new card, turns out the payment just kept getting declined. This is really sad, what's going on?"

Keyphrases:
1810it [1:02:11,  1.56s/it]
ChatCompletion(id='chatcmpl-9Mz3pnnT2F63icBJpshD6UV4HTqK5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment declined", "card not working", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715264961, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=250, total_tokens=263))
["payment declined", "card not working", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was a transaction on my card declined?"

Keyphrases:
1811it [1:02:13,  1.63s/it]
ChatCompletion(id='chatcmpl-9Mz3qfo8FDwWv0C1GWipTK4nm9GJh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction decline", "declined payment", "card declined"]', role='assistant', function_call=None, tool_calls=None))], created=1715264962, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["transaction decline", "declined payment", "card declined"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My new card keeps getting declined. I was very excited to use it for the first time today. Why is this doing this?"

Keyphrases:
1812it [1:02:15,  1.65s/it]
ChatCompletion(id='chatcmpl-9Mz3s3qKacSZqmiY4epI3Gjbtgg0G', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "transaction issue", "new card problems"]', role='assistant', function_call=None, tool_calls=None))], created=1715264964, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=244, total_tokens=257))
["card declined", "transaction issue", "new card problems"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My latest payment was declined, I was told everything was back to working order. What happened?"

Keyphrases:
1813it [1:02:17,  1.63s/it]
ChatCompletion(id='chatcmpl-9Mz3tMwnr05k8S80PT0erOT9RZlZA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment declined", "declined transaction resolution", "transaction status"]', role='assistant', function_call=None, tool_calls=None))], created=1715264965, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=237, total_tokens=251))
["payment declined", "declined transaction resolution", "transaction status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I know I have enough funds in my account but my card payment hasn't worked for some reason. What do I do?"

Keyphrases:
1814it [1:02:19,  1.80s/it]
ChatCompletion(id='chatcmpl-9Mz3vm1QjmRFS11Sf5HCQNVc3GWna', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment issue", "card declined", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715264967, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=243, total_tokens=255))
["payment issue", "card declined", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why doesn't the card payment work"

Keyphrases:
1815it [1:02:20,  1.66s/it]
ChatCompletion(id='chatcmpl-9Mz3xFeLucK34RzaawjgFgE5yGdeY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment issue", "card not working", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715264969, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["payment issue", "card not working", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm really stuck. I don't know why but my card payment has not gone through."

Keyphrases:
1816it [1:02:26,  2.96s/it]
ChatCompletion(id='chatcmpl-9Mz3yhInYf81u3YKEnHyvPtiVtQIs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment issue", "card payment failure", "transaction declined"]', role='assistant', function_call=None, tool_calls=None))], created=1715264970, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=237, total_tokens=250))
["payment issue", "card payment failure", "transaction declined"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a card payment that was declined, but why?"

Keyphrases:
1817it [1:02:28,  2.51s/it]
ChatCompletion(id='chatcmpl-9Mz44XiWtXh5AkmGFT9gwZVxVoPqB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment declined", "declined card transaction", "reason for declined payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715264976, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["payment declined", "declined card transaction", "reason for declined payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you know why my card payment did not work?"

Keyphrases:
1818it [1:02:29,  2.16s/it]
ChatCompletion(id='chatcmpl-9Mz46p46jwodICyj7n36z8ClRlQEm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment issue", "payment failure", "transaction declined"]', role='assistant', function_call=None, tool_calls=None))], created=1715264978, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["card payment issue", "payment failure", "transaction declined"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Something is wrong with my payment account since it has been declined"

Keyphrases:
1819it [1:02:30,  1.87s/it]
ChatCompletion(id='chatcmpl-9Mz47Nu3zW9c4m99oxtxzDUxYJbiS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment issue", "declined payment", "account problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264979, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["payment issue", "declined payment", "account problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why are you declining my payment? Everything was fine."

Keyphrases:
1820it [1:02:32,  1.86s/it]
ChatCompletion(id='chatcmpl-9Mz48KsTsFnLV2S16pM7I5dun6vGt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment declined", "transaction issues", "declined card"]', role='assistant', function_call=None, tool_calls=None))], created=1715264980, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["payment declined", "transaction issues", "declined card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't know why my payment didn't work."

Keyphrases:
1821it [1:02:34,  2.07s/it]
ChatCompletion(id='chatcmpl-9Mz4BCaAJAFXJTT9YlwG3TCgLREvl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment failure", "transaction error", "failed payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715264983, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["payment failure", "transaction error", "failed payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card payment did not work."

Keyphrases:
1822it [1:02:37,  2.10s/it]
ChatCompletion(id='chatcmpl-9Mz4DPuAPqVmPg9KkpNVHwnw0qAm4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment issue", "card declined", "transaction problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715264985, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["payment issue", "card declined", "transaction problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my debit card being declined when I have money?"

Keyphrases:
1823it [1:02:39,  2.05s/it]
ChatCompletion(id='chatcmpl-9Mz4FaUX5I8cAhDhLLo78U1fjDVFK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "sufficient balance issue", "transaction denial"]', role='assistant', function_call=None, tool_calls=None))], created=1715264987, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["card declined", "sufficient balance issue", "transaction denial"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card was not accepted."

Keyphrases:
1824it [1:02:40,  1.80s/it]
ChatCompletion(id='chatcmpl-9Mz4H26YYuvN6qLaVmnVTkKNJWuV5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card rejection", "payment declined", "card not accepted"]', role='assistant', function_call=None, tool_calls=None))], created=1715264989, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["card rejection", "payment declined", "card not accepted"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have no idea why my card payment did not work."

Keyphrases:
1825it [1:02:43,  2.09s/it]
ChatCompletion(id='chatcmpl-9Mz4IDzaCLG28Y9J1Pic5LFkAMVfZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment issue", "payment failure", "declined card transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264990, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["card payment issue", "payment failure", "declined card transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card payment didn't work, can you help?"

Keyphrases:
1826it [1:02:45,  2.05s/it]
ChatCompletion(id='chatcmpl-9Mz4LAIAwEvRtYcSVS1aphlRKnYVU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment issue", "card payment failure", "transaction support"]', role='assistant', function_call=None, tool_calls=None))], created=1715264993, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["payment issue", "card payment failure", "transaction support"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card was rejected at the store for some reason, can you look into this for me?"

Keyphrases:
1827it [1:02:46,  1.80s/it]
ChatCompletion(id='chatcmpl-9Mz4NlOoQS4c3NNV15TEJBDnLJjU3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card rejection", "transaction issue", "payment declined"]', role='assistant', function_call=None, tool_calls=None))], created=1715264995, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=237, total_tokens=249))
["card rejection", "transaction issue", "payment declined"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please explain why my card was declined?"

Keyphrases:
1828it [1:02:47,  1.60s/it]
ChatCompletion(id='chatcmpl-9Mz4OQC1k31nDMmmXHxNtKvu0TvwT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "declined transaction", "transaction issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715264996, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card declined", "declined transaction", "transaction issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hello, I am facing the issue with my new card as payments are declining again and again. Please help me in this issue."

Keyphrases:
1829it [1:02:48,  1.46s/it]
ChatCompletion(id='chatcmpl-9Mz4Pc1msKLbxhx8bM5poSubvGNCD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment declined", "card not working", "transaction issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715264997, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=244, total_tokens=257))
["payment declined", "card not working", "transaction issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you know why my card payment is declined?"

Keyphrases:
1830it [1:02:50,  1.53s/it]
ChatCompletion(id='chatcmpl-9Mz4Qzlmxb6s8qgRgvZxouGWAWOm0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment issue", "payment declined", "declined transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715264998, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["card payment issue", "payment declined", "declined transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was my Payment declined"

Keyphrases:
1831it [1:02:51,  1.51s/it]
ChatCompletion(id='chatcmpl-9Mz4SqGg1bWnNFZAVA6nS9LcC0gzA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment declined", "declined transaction", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265000, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["payment declined", "declined transaction", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "They declined my card payment."

Keyphrases:
1832it [1:02:53,  1.67s/it]
ChatCompletion(id='chatcmpl-9Mz4TnQeS0BuYRtfgehAvqZxl4bEi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["declined payment", "card declined", "payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265001, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["declined payment", "card declined", "payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why has my card payment been declined?"

Keyphrases:
1833it [1:02:55,  1.57s/it]
ChatCompletion(id='chatcmpl-9Mz4VIRQcwtUdqg3EcT2AX0vm418Y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment declined", "card declined", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715265003, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["payment declined", "card declined", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I finally got my new card and was very excited to use it today. However, my payment kept declining. What is happening?"

Keyphrases:
1834it [1:03:01,  2.91s/it]
ChatCompletion(id='chatcmpl-9Mz4Xr6xFU2k7iEW2oINIoOrbbF9L', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment declined", "card not working", "transaction issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715265005, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=244, total_tokens=257))
["payment declined", "card not working", "transaction issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card payment did not complete."

Keyphrases:
1835it [1:03:02,  2.47s/it]
ChatCompletion(id='chatcmpl-9Mz4dtD5UOwFjBkibrbHj6kg1OTBS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment issue", "card payment failure", "transaction incomplete"]', role='assistant', function_call=None, tool_calls=None))], created=1715265011, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["payment issue", "card payment failure", "transaction incomplete"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card didn't work in one of the shops."

Keyphrases:
1836it [1:03:03,  2.09s/it]
ChatCompletion(id='chatcmpl-9Mz4ePwZ54o0Oat3nUcCmbokNhnse', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card decline", "card not working", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265012, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["card decline", "card not working", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Card payment declined?"

Keyphrases:
1837it [1:03:05,  1.86s/it]
ChatCompletion(id='chatcmpl-9Mz4gEu2vy6tmRUZRCgsVwXUPl5Py', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment issue", "declined transaction", "card payment failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715265014, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=222, total_tokens=236))
["payment issue", "declined transaction", "card payment failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried using my card and it kept getting declined, Why?"

Keyphrases:
1838it [1:03:06,  1.79s/it]
ChatCompletion(id='chatcmpl-9Mz4hSdKZnfCumyRY8eEen1Qt79Sf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "transaction issue", "payment rejection"]', role='assistant', function_call=None, tool_calls=None))], created=1715265015, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["card declined", "transaction issue", "payment rejection"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do you fix  my card payment?"

Keyphrases:
1839it [1:03:10,  2.44s/it]
ChatCompletion(id='chatcmpl-9Mz4kcR4KMyr37DBaEbSPi5C0Bmah', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment issue", "fix payment", "payment troubleshooting"]', role='assistant', function_call=None, tool_calls=None))], created=1715265018, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["card payment issue", "fix payment", "payment troubleshooting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do you keep declining my payment? I tried several times already with this card and it's just not working"

Keyphrases:
1840it [1:03:12,  2.13s/it]
ChatCompletion(id='chatcmpl-9Mz4mQZm3FZt3z9038Dr0XrR2wMWT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment declined", "card issue", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715265020, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=241, total_tokens=253))
["payment declined", "card issue", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I did transfer, why is it pending"

Keyphrases:
1841it [1:03:13,  1.99s/it]
ChatCompletion(id='chatcmpl-9Mz4onC5IITBQBfpDPxTCcrZR29Ud', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "delayed transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265022, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["pending transfer", "transfer status", "delayed transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long for money transfer to show?"

Keyphrases:
1842it [1:03:15,  1.88s/it]
ChatCompletion(id='chatcmpl-9Mz4pr1yJm8ZkRoRrJOsSJm2OpMii', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer time", "money transfer processing", "transfer delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715265023, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["transfer time", "money transfer processing", "transfer delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my transfer not done yet?"

Keyphrases:
1843it [1:03:16,  1.69s/it]
ChatCompletion(id='chatcmpl-9Mz4ruNqLM8ryMZsP6TWJi94vEsax', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer delay", "transfer status"]', role='assistant', function_call=None, tool_calls=None))], created=1715265025, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["pending transfer", "transfer delay", "transfer status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a pending transfer"

Keyphrases:
1844it [1:03:17,  1.57s/it]
ChatCompletion(id='chatcmpl-9Mz4sJR979A2xJpeqE89dtp1NpiCT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "transaction pending"]', role='assistant', function_call=None, tool_calls=None))], created=1715265026, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["pending transfer", "transfer status", "transaction pending"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am waiting for a pending money transfer to process."

Keyphrases:
1845it [1:03:19,  1.54s/it]
ChatCompletion(id='chatcmpl-9Mz4urhyso8bdvUGgyOPev98OGoKv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "money transfer status", "transfer delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715265028, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["pending transfer", "money transfer status", "transfer delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "i transfered however its still pending"

Keyphrases:
1846it [1:03:21,  1.74s/it]
ChatCompletion(id='chatcmpl-9Mz4vYrePrV8NysOYnEuNaBVx45IR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "delayed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265029, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["pending transfer", "transfer status", "delayed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a transfer that's pending and wanted to know how long it is going to take to process?"

Keyphrases:
1847it [1:03:23,  1.66s/it]
ChatCompletion(id='chatcmpl-9Mz4xJCnB0ih27ko7SWheZt39MGb4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer duration", "transfer processing time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265031, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=239, total_tokens=252))
["pending transfer", "transfer duration", "transfer processing time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "So the transfer finally worked but now it's been pending for quite a long time. How long do you expect me to wait for it? It's quite urgent"

Keyphrases:
1848it [1:03:25,  1.93s/it]
ChatCompletion(id='chatcmpl-9Mz4zZyphtkheP8elErIYoWfvxVSq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer delay", "urgent transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265033, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=251, total_tokens=263))
["pending transfer", "transfer delay", "urgent transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I had made a transfer but its still pending."

Keyphrases:
1849it [1:03:27,  2.05s/it]
ChatCompletion(id='chatcmpl-9Mz521JYzqxcgO0cyJQo79YlS8Dof', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "delayed transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265036, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["pending transfer", "transfer status", "delayed transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I submitted my transfer but it has been pending for quite a while and I was wondering what takes so long? why hasn't it completed"

Keyphrases:
1850it [1:03:30,  2.30s/it]
ChatCompletion(id='chatcmpl-9Mz546h9sisVXpPvK2cBX5JzmuCnW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer delay", "transfer status"]', role='assistant', function_call=None, tool_calls=None))], created=1715265038, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=246, total_tokens=258))
["pending transfer", "transfer delay", "transfer status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I speed up a transfer?  Mine is pending."

Keyphrases:
1851it [1:03:32,  2.02s/it]
ChatCompletion(id='chatcmpl-9Mz57ki3tvc3G0TrDfGtZBr3r34Te', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["speed up transfer", "pending transfer", "transfer acceleration"]', role='assistant', function_call=None, tool_calls=None))], created=1715265041, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["speed up transfer", "pending transfer", "transfer acceleration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long can an EU transfer take?"

Keyphrases:
1852it [1:03:34,  1.99s/it]
ChatCompletion(id='chatcmpl-9Mz58X6Xzlb6bDrNt2J8z3dEBtZlC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["EU transfer duration", "transfer time", "international transfer time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265042, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["EU transfer duration", "transfer time", "international transfer time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer is still coming up as pending."

Keyphrases:
1853it [1:03:35,  1.76s/it]
ChatCompletion(id='chatcmpl-9Mz5AUkYRxZkXbUjy8TBLQYUIOhKz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "delayed transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265044, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["pending transfer", "transfer status", "delayed transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm trying to transfer money to another country. It's just pending and not sending. My account details are correct. Please help me."

Keyphrases:
1854it [1:03:38,  2.22s/it]
ChatCompletion(id='chatcmpl-9Mz5BfQZ3ZamObC6bZk1d0XwuUrj2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international transfer issue", "pending transaction", "transfer not sending"]', role='assistant', function_call=None, tool_calls=None))], created=1715265045, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=246, total_tokens=260))
["international transfer issue", "pending transaction", "transfer not sending"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer is still pending and I know the account numbers are correct.  Please help."

Keyphrases:
1855it [1:03:40,  1.98s/it]
ChatCompletion(id='chatcmpl-9Mz5EYpVCqdidBo5Epbd1o8qKB7mm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "account verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715265048, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=236, total_tokens=248))
["pending transfer", "transfer status", "account verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I transferred money yesterday, but it still isn't available?"

Keyphrases:
1856it [1:03:41,  1.81s/it]
ChatCompletion(id='chatcmpl-9Mz5GKDjuELoxkdQL8tBSdEGhML9y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer status", "delayed transfer", "transfer not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715265050, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["money transfer status", "delayed transfer", "transfer not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does a transfer stay pending?"

Keyphrases:
1857it [1:03:43,  1.80s/it]
ChatCompletion(id='chatcmpl-9Mz5H4KnZdSYruobJwIAGBXjtQlnC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer duration", "transfer status", "delayed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265051, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["pending transfer duration", "transfer status", "delayed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long do transfer pend for?"

Keyphrases:
1858it [1:03:44,  1.69s/it]
ChatCompletion(id='chatcmpl-9Mz5J6Rv4oPJtHuHBtNC0i2dMzSx5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer duration", "transfer delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715265053, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["pending transfer", "transfer duration", "transfer delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why hasn't my transfer gone through yet?"

Keyphrases:
1859it [1:03:46,  1.66s/it]
ChatCompletion(id='chatcmpl-9Mz5LotpO48N8EV1MOnJyZYl4K70e', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer status", "delayed transfer", "transfer not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715265055, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["transfer status", "delayed transfer", "transfer not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will the transfer go through?"

Keyphrases:
1860it [1:03:50,  2.38s/it]
ChatCompletion(id='chatcmpl-9Mz5M0Ffo2cvxvxq1lxEQ0KUfIp9V', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer status", "transfer completion time", "expected transfer date"]', role='assistant', function_call=None, tool_calls=None))], created=1715265056, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["transfer status", "transfer completion time", "expected transfer date"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please explain why the transfers shows up as pending?"

Keyphrases:
1861it [1:03:51,  2.00s/it]
ChatCompletion(id='chatcmpl-9Mz5QX8PdHENRCYChwvUD7v14J78j', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "reason for delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715265060, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["pending transfer", "transfer status", "reason for delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I double checked that I have the correct account details , they're right for sure. Transfer is still pending since forever. What should be done now?"

Keyphrases:
1862it [1:03:54,  2.23s/it]
ChatCompletion(id='chatcmpl-9Mz5RJL2DMUpiVtrCyXOE1UD7DljH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer delay", "resolve transfer issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265061, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=248, total_tokens=261))
["pending transfer", "transfer delay", "resolve transfer issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will my transfer go through?"

Keyphrases:
1863it [1:03:55,  1.97s/it]
ChatCompletion(id='chatcmpl-9Mz5UMLwG0OeIs0p8Vpgrlc1l2fmq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer status", "expected transfer time", "transfer completion"]', role='assistant', function_call=None, tool_calls=None))], created=1715265064, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["transfer status", "expected transfer time", "transfer completion"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the cause that the transfer shows as pending?"

Keyphrases:
1864it [1:03:56,  1.74s/it]
ChatCompletion(id='chatcmpl-9Mz5VNU4fMXV9x341AIO7iTYMrI2w', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "reason for delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715265065, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["pending transfer", "transfer status", "reason for delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will the transfer be completed?"

Keyphrases:
1865it [1:03:58,  1.64s/it]
ChatCompletion(id='chatcmpl-9Mz5Xe5gkwXzN6pxzsN2HrwgGu8NJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer status", "completion time", "transfer ETA"]', role='assistant', function_call=None, tool_calls=None))], created=1715265067, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["transfer status", "completion time", "transfer ETA"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Pending transfer?"

Keyphrases:
1866it [1:03:59,  1.53s/it]
ChatCompletion(id='chatcmpl-9Mz5YHkkJjyvHvfz0dbnw4vbqApkj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transaction", "transaction status", "transfer delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715265068, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=221, total_tokens=233))
["pending transaction", "transaction status", "transfer delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to know why my payment is still pending, can you help?"

Keyphrases:
1867it [1:04:01,  1.61s/it]
ChatCompletion(id='chatcmpl-9Mz5Z52uxhP8uew8hK1P1seGtiJBu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending payment", "payment status", "help with payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715265069, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["pending payment", "payment status", "help with payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone transferred money to me and it doesn't show"

Keyphrases:
1868it [1:04:04,  2.00s/it]
ChatCompletion(id='chatcmpl-9Mz5bznv04NN5owxx2TYimU0ZTkcy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "transfer not received", "transfer issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265071, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["missing transfer", "transfer not received", "transfer issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does a transfer take to be confirmed?"

Keyphrases:
1869it [1:04:05,  1.86s/it]
ChatCompletion(id='chatcmpl-9Mz5eydEvozIfH0bTAQmty1AHXDCe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer confirmation time", "transfer duration", "transaction processing time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265074, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["transfer confirmation time", "transfer duration", "transaction processing time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a transfer 12 hours ago. Why is it still listed as pending?"

Keyphrases:
1870it [1:04:06,  1.70s/it]
ChatCompletion(id='chatcmpl-9Mz5fk5wj4ubJ2VhWrjUS6XeS73en', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "delayed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265075, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=235, total_tokens=248))
["pending transfer", "transfer status", "delayed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why does my transfer say "pending"?"

Keyphrases:
1871it [1:04:08,  1.59s/it]
ChatCompletion(id='chatcmpl-9Mz5hrshRk1BUDijD9P9OcWMK18zI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "transfer delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715265077, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["pending transfer", "transfer status", "transfer delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long can I expect a transfer to pend for?"

Keyphrases:
1872it [1:04:09,  1.54s/it]
ChatCompletion(id='chatcmpl-9Mz5it46LGJ13c9B7nQkH4cJ8vkk0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer duration", "transfer delay", "expected wait time for transfers"]', role='assistant', function_call=None, tool_calls=None))], created=1715265078, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["pending transfer duration", "transfer delay", "expected wait time for transfers"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "For how long will my transfer be pending?"

Keyphrases:
1873it [1:04:11,  1.73s/it]
ChatCompletion(id='chatcmpl-9Mz5kDM13qeHAXS3Xv9ewVwgiIqXN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer duration", "transfer status"]', role='assistant', function_call=None, tool_calls=None))], created=1715265080, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["pending transfer", "transfer duration", "transfer status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Transferring money in 2018 to another country shouldn't take this long. My transfer has been pending for too long. I verified my account details are correct."

Keyphrases:
1874it [1:04:12,  1.54s/it]
ChatCompletion(id='chatcmpl-9Mz5mJudMMpE2xf1gdbZBCZsOxpDC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international transfer delay", "pending transfer", "transfer verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715265082, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=252, total_tokens=265))
["international transfer delay", "pending transfer", "transfer verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is a money transfer not showing?"

Keyphrases:
1875it [1:04:14,  1.61s/it]
ChatCompletion(id='chatcmpl-9Mz5nFHfe5ubV8aO65X8jYHuzIBqc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "transfer not visible", "delayed transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265083, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["missing transfer", "transfer not visible", "delayed transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The transfer is coming up as pending the payment is due today. Will I be charged a fee?"

Keyphrases:
1876it [1:04:16,  1.65s/it]
ChatCompletion(id='chatcmpl-9Mz5pdvgqJsiPas0Ld8xTcarsnkLQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer fee", "payment due"]', role='assistant', function_call=None, tool_calls=None))], created=1715265085, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=238, total_tokens=250))
["pending transfer", "transfer fee", "payment due"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am still waiting for a money transfer to show"

Keyphrases:
1877it [1:04:17,  1.60s/it]
ChatCompletion(id='chatcmpl-9Mz5qWNx2wU2vGUtZfcakSIZekDbn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer delay", "awaiting funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715265086, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["pending transfer", "transfer delay", "awaiting funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer hasn't gone through yet."

Keyphrases:
1878it [1:04:19,  1.55s/it]
ChatCompletion(id='chatcmpl-9Mz5suBNWIEWt8heyqVb2WaIqBVnE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer delay", "transfer status"]', role='assistant', function_call=None, tool_calls=None))], created=1715265088, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["pending transfer", "transfer delay", "transfer status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am confused as to why my transfer could still be pending."

Keyphrases:
1879it [1:04:22,  1.96s/it]
ChatCompletion(id='chatcmpl-9Mz5t1fa4DnjZmDUE2Ih9nuYTXkSV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "delayed transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265089, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["pending transfer", "transfer status", "delayed transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does it take for a money transfer to show?"

Keyphrases:
1880it [1:04:23,  1.85s/it]
ChatCompletion(id='chatcmpl-9Mz5wt43nfyjHBu8leGgg0LcKyStP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer time", "money transfer processing", "transfer delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715265092, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["transfer time", "money transfer processing", "transfer delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you remove my account please?"

Keyphrases:
1881it [1:04:26,  1.98s/it]
ChatCompletion(id='chatcmpl-9Mz5yI9OmheWnmfjWC3rsVeRYhcUC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "close account", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265094, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["account deletion", "close account", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "i want to close an account but im not sure about setting up a new one in the future, what do you recommend"

Keyphrases:
1882it [1:04:28,  1.95s/it]
ChatCompletion(id='chatcmpl-9Mz60hj0hXVksKWjHcuoeK5HMWLn0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account closure", "future banking options", "closing account advice"]', role='assistant', function_call=None, tool_calls=None))], created=1715265096, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=243, total_tokens=257))
["account closure", "future banking options", "closing account advice"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My account needs to be deleted."

Keyphrases:
1883it [1:04:30,  2.05s/it]
ChatCompletion(id='chatcmpl-9Mz62SMs4jXxikj8foUqTVREMoJzO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["delete account", "account closure", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265098, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["delete account", "account closure", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to delete my account please."

Keyphrases:
1884it [1:04:36,  3.42s/it]
ChatCompletion(id='chatcmpl-9Mz69sCnKWmc8pTjf0P9DoVCM2oU1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "close account", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265105, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["account deletion", "close account", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What steps do I need to take to close my account?"

Keyphrases:
1885it [1:04:38,  2.79s/it]
ChatCompletion(id='chatcmpl-9Mz6B5TkaCD8mSjEMTyEgpw370LEE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["close account", "account termination", "terminate banking account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265107, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["close account", "account termination", "terminate banking account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm tired of all the problems I've had. I want to quit this account!"

Keyphrases:
1886it [1:04:39,  2.38s/it]
ChatCompletion(id='chatcmpl-9Mz6CM4ozWLI6IKn7xTntFj9SKrpk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["close account", "account termination", "end banking services"]', role='assistant', function_call=None, tool_calls=None))], created=1715265108, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=236, total_tokens=249))
["close account", "account termination", "end banking services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please delete my account right now!"

Keyphrases:
1887it [1:04:41,  2.32s/it]
ChatCompletion(id='chatcmpl-9Mz6Dzf5Uu2RxzhRfcNTkNDrauvhF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "close account", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265109, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["account deletion", "close account", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to close my account"

Keyphrases:
1888it [1:04:43,  2.04s/it]
ChatCompletion(id='chatcmpl-9Mz6GEHZeBrpguU03iq6QbLfsq5Rn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["close account", "account termination", "terminate banking services"]', role='assistant', function_call=None, tool_calls=None))], created=1715265112, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["close account", "account termination", "terminate banking services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "unhappy with you, how to delete account"

Keyphrases:
1889it [1:04:44,  1.87s/it]
ChatCompletion(id='chatcmpl-9Mz6HLZLTfmYktnWEsu8oiLbw9Nkq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "close account", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265113, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["account deletion", "close account", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to delete my account."

Keyphrases:
1890it [1:04:46,  1.75s/it]
ChatCompletion(id='chatcmpl-9Mz6JSVeO8HlM7Cdv2XxqtvMB4Pzx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "close account", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265115, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["account deletion", "close account", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am highly unsatisfied with this company and want to delete my account!"

Keyphrases:
1891it [1:04:47,  1.69s/it]
ChatCompletion(id='chatcmpl-9Mz6K5JDy2CKeZB47jgmoxGLDVoQg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "terminate account", "close account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265116, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=233, total_tokens=245))
["account deletion", "terminate account", "close account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't like your company. Delete my account."

Keyphrases:
1892it [1:04:49,  1.60s/it]
ChatCompletion(id='chatcmpl-9Mz6M6SmUUQk5fwVyi1CcnPZkpXUd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "delete account", "terminate services"]', role='assistant', function_call=None, tool_calls=None))], created=1715265118, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["account deletion", "delete account", "terminate services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to close my account."

Keyphrases:
1893it [1:04:50,  1.55s/it]
ChatCompletion(id='chatcmpl-9Mz6Nv0olwiJYNUSrx4DAJULzg3qv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["close account", "account termination", "terminate banking services"]', role='assistant', function_call=None, tool_calls=None))], created=1715265119, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["close account", "account termination", "terminate banking services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "This company is terrible! Can you delete my account?"

Keyphrases:
1894it [1:04:51,  1.48s/it]
ChatCompletion(id='chatcmpl-9Mz6OVCJqGM4GOzLEmBUhaF0e9VoI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "delete account", "close account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265120, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["account deletion", "delete account", "close account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "This company is bad, please delete my account."

Keyphrases:
1895it [1:04:53,  1.59s/it]
ChatCompletion(id='chatcmpl-9Mz6QS7gKy7zmrTfjJhw1rdEoSwOL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "delete account", "close account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265122, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["account deletion", "delete account", "close account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "please delete my account, your services are not up to par."

Keyphrases:
1896it [1:04:55,  1.51s/it]
ChatCompletion(id='chatcmpl-9Mz6RskewEsa373zQCNqkNafkcSBm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "terminate account", "close account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265123, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["account deletion", "terminate account", "close account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need your help in deleting my account."

Keyphrases:
1897it [1:04:56,  1.55s/it]
ChatCompletion(id='chatcmpl-9Mz6TG5PcuLxo3DekbqoRYY2nzcPo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["delete account", "account closure", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265125, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["delete account", "account closure", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The service of this company sucks, I need to terminate my account."

Keyphrases:
1898it [1:04:58,  1.52s/it]
ChatCompletion(id='chatcmpl-9Mz6V0KG6x0hDw9Q890WsBX1tbwtc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["terminate account", "close account", "account cancellation"]', role='assistant', function_call=None, tool_calls=None))], created=1715265127, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["terminate account", "close account", "account cancellation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Delete this account!"

Keyphrases:
1899it [1:05:00,  1.77s/it]
ChatCompletion(id='chatcmpl-9Mz6WMTyR8gPK7vQG3vEZdRoEyAX7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "close account", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265128, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=222, total_tokens=234))
["account deletion", "close account", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I get rid of my account ASAP?"

Keyphrases:
1900it [1:05:02,  1.85s/it]
ChatCompletion(id='chatcmpl-9Mz6YtM9bhHdjJci4kpKw9qkuMABP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["close account", "account termination", "terminate account immediately"]', role='assistant', function_call=None, tool_calls=None))], created=1715265130, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["close account", "account termination", "terminate account immediately"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "This company isn't good, I would like to delete my account."

Keyphrases:
1901it [1:05:03,  1.73s/it]
ChatCompletion(id='chatcmpl-9Mz6aZMIiVh8zaFyWlXDiSg7uDkDD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "cancel account", "close account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265132, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["account deletion", "cancel account", "close account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you delete my account please?"

Keyphrases:
1902it [1:05:05,  1.56s/it]
ChatCompletion(id='chatcmpl-9Mz6c2bS4r8RNsxyiDGpHrVALjFXH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "close account", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265134, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["account deletion", "close account", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am not satisfied with your company and would like to delete my accounts!"

Keyphrases:
1903it [1:05:07,  1.72s/it]
ChatCompletion(id='chatcmpl-9Mz6dExE1Y2mJUO3vkjy0IzhCumMz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account closure", "delete account", "dissatisfaction response"]', role='assistant', function_call=None, tool_calls=None))], created=1715265135, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["account closure", "delete account", "dissatisfaction response"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please delete my account. I am not happy with the service from your company."

Keyphrases:
1904it [1:05:09,  1.76s/it]
ChatCompletion(id='chatcmpl-9Mz6fGtMECbcc0WxRp2LKQDEDkJYP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "terminate account", "close account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265137, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=234, total_tokens=246))
["account deletion", "terminate account", "close account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please terminate my account."

Keyphrases:
1905it [1:05:10,  1.78s/it]
ChatCompletion(id='chatcmpl-9Mz6hGLm5J7lhRDvD6Ook0fxOyu5F', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account termination", "close account", "end banking services"]', role='assistant', function_call=None, tool_calls=None))], created=1715265139, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["account termination", "close account", "end banking services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am sick of this damn company and want to close out my account."

Keyphrases:
1906it [1:05:12,  1.83s/it]
ChatCompletion(id='chatcmpl-9Mz6jrWAQX65LN3r8U4ElBIcBIGuE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account closure", "close account", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265141, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=233, total_tokens=245))
["account closure", "close account", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please close my account. I am unsatisfied with your service."

Keyphrases:
1907it [1:05:14,  1.65s/it]
ChatCompletion(id='chatcmpl-9Mz6l4TDyzANjh3Xxj7rlQ62QvGjV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account closure", "terminate account", "unsatisfied customer service"]', role='assistant', function_call=None, tool_calls=None))], created=1715265143, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["account closure", "terminate account", "unsatisfied customer service"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please delete my account."

Keyphrases:
1908it [1:05:16,  1.74s/it]
ChatCompletion(id='chatcmpl-9Mz6mZAX3bMxUmrTysgFK47PKKGbH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["delete account", "account closure", "close account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265144, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["delete account", "account closure", "close account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Your service is terrible,.  Delete my account,"

Keyphrases:
1909it [1:05:17,  1.56s/it]
ChatCompletion(id='chatcmpl-9Mz6oAFXhjGSu32ZVJbwmwGrbkgb6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "terminate account", "delete account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265146, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["account deletion", "terminate account", "delete account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want my account deleted!"

Keyphrases:
1910it [1:05:18,  1.46s/it]
ChatCompletion(id='chatcmpl-9Mz6pLXCyZU7qp3LNwen34B6X918W', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "delete banking account", "close account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265147, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["account deletion", "delete banking account", "close account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am extremely unhappy with this app and want to get rid of my account?"

Keyphrases:
1911it [1:05:20,  1.54s/it]
ChatCompletion(id='chatcmpl-9Mz6qirmSEIhHsHhgYScbHdeiK5PO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "close account", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265148, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=234, total_tokens=246))
["account deletion", "close account", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I delete my account?"

Keyphrases:
1912it [1:05:21,  1.52s/it]
ChatCompletion(id='chatcmpl-9Mz6sNcv6rHND13sdiIlu7mPwmXwp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "close account", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265150, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["account deletion", "close account", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "This company sucks! Can you delete my account?"

Keyphrases:
1913it [1:05:23,  1.58s/it]
ChatCompletion(id='chatcmpl-9Mz6tby9XOouJwolA35IocrJOXsiU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "delete account", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265151, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["account deletion", "delete account", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I wish to close my account. I do not like the service you provide."

Keyphrases:
1914it [1:05:25,  1.65s/it]
ChatCompletion(id='chatcmpl-9Mz6vqbkV52402XY0Rcw6HKt3AGF1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["close account", "account closure", "terminate account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265153, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=234, total_tokens=246))
["close account", "account closure", "terminate account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you help me get rid of my account?"

Keyphrases:
1915it [1:05:34,  3.87s/it]
ChatCompletion(id='chatcmpl-9Mz6xheLyDKyv9HHfn0VmM3shxCLK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["close account", "account termination", "delete account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265155, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["close account", "account termination", "delete account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't find your services useful anymore, how do I delete my account?"

Keyphrases:
1916it [1:05:36,  3.29s/it]
ChatCompletion(id='chatcmpl-9Mz76kdTbug9XzOA1vzg92kryssIr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "close account", "terminate services"]', role='assistant', function_call=None, tool_calls=None))], created=1715265164, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=234, total_tokens=246))
["account deletion", "close account", "terminate services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please delete my account, this company is not working for me!"

Keyphrases:
1917it [1:05:37,  2.85s/it]
ChatCompletion(id='chatcmpl-9Mz78vrGB7YyKoKSGzdcUjpzhGphP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "close account", "terminate services"]', role='assistant', function_call=None, tool_calls=None))], created=1715265166, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["account deletion", "close account", "terminate services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to delete my account. I'm unhappy with the service you're providing."

Keyphrases:
1918it [1:05:40,  2.65s/it]
ChatCompletion(id='chatcmpl-9Mz7AqYKb2v9xJNcvLTgJdCG7ME1g', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account deletion", "terminate account", "dissatisfaction response"]', role='assistant', function_call=None, tool_calls=None))], created=1715265168, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["account deletion", "terminate account", "dissatisfaction response"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me how to close my account?"

Keyphrases:
1919it [1:05:43,  2.75s/it]
ChatCompletion(id='chatcmpl-9Mz7CRopYdBSCGUVfwbhG7HmOI1VJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["close account", "account termination", "terminate banking account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265170, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["close account", "account termination", "terminate banking account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "This company sucks! Can you terminate my account?"

Keyphrases:
1920it [1:05:44,  2.38s/it]
ChatCompletion(id='chatcmpl-9Mz7FdZMkDz3KyP5PLSgChZBwMxGA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["terminate account", "close account", "account cancellation"]', role='assistant', function_call=None, tool_calls=None))], created=1715265173, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["terminate account", "close account", "account cancellation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do if an ATM "stole" my card?"

Keyphrases:
1921it [1:05:46,  2.18s/it]
ChatCompletion(id='chatcmpl-9Mz7G19MSh3GkRVTBw2KcFRTUEHDZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card issue", "card retrieval", "stolen card by ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265174, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=17, prompt_tokens=232, total_tokens=249))
["ATM card issue", "card retrieval", "stolen card by ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I retrieve my card from the machine?"

Keyphrases:
1922it [1:05:47,  1.90s/it]
ChatCompletion(id='chatcmpl-9Mz7Izr3IpRsOLYRXussOc5cV6YSV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card retrieval", "stuck card", "ATM card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265176, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["card retrieval", "stuck card", "ATM card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was retrieving money and my card wouldn't remove."

Keyphrases:
1923it [1:05:50,  2.22s/it]
ChatCompletion(id='chatcmpl-9Mz7Jas7VZq642OkRQqtnKsBE9mdE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card stuck", "ATM issue", "withdrawal problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265177, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["card stuck", "ATM issue", "withdrawal problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do since the machine swallowed my card. I need one."

Keyphrases:
1924it [1:05:53,  2.36s/it]
ChatCompletion(id='chatcmpl-9Mz7MhbbS6N6heH2fy6J8ze6ADsJX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card retrieval", "swallowed card", "replacement card"]', role='assistant', function_call=None, tool_calls=None))], created=1715265180, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["card retrieval", "swallowed card", "replacement card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "HOw do I get my card back after the ATM has pulled it in?"

Keyphrases:
1925it [1:05:55,  2.45s/it]
ChatCompletion(id='chatcmpl-9Mz7PoMmw6lEMFd95Tu0Q2KAr4fTY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["retrieving card", "ATM card retention", "card stuck in ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265183, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=234, total_tokens=252))
["retrieving card", "ATM card retention", "card stuck in ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Atm took my card"

Keyphrases:
1926it [1:05:58,  2.54s/it]
ChatCompletion(id='chatcmpl-9Mz7SLEiWPLqKtAxxlUoL7X04zFLs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card retrieval", "ATM card issue", "card stuck in ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265186, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=224, total_tokens=240))
["card retrieval", "ATM card issue", "card stuck in ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a way I can get my ATM card back from the machine?"

Keyphrases:
1927it [1:06:00,  2.24s/it]
ChatCompletion(id='chatcmpl-9Mz7U9aSImsh8U37lWovjdDh7eaZK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["retrieve ATM card", "ATM card retrieval", "card stuck in machine"]', role='assistant', function_call=None, tool_calls=None))], created=1715265188, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=17, prompt_tokens=233, total_tokens=250))
["retrieve ATM card", "ATM card retrieval", "card stuck in machine"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think the atm ate my card."

Keyphrases:
1928it [1:06:01,  2.09s/it]
ChatCompletion(id='chatcmpl-9Mz7W24iQm2VBqHHMVHTSkVJTWxQY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "card retrieval", "card stuck"]', role='assistant', function_call=None, tool_calls=None))], created=1715265190, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["ATM issue", "card retrieval", "card stuck"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM didn't give me the card back!"

Keyphrases:
1929it [1:06:03,  1.92s/it]
ChatCompletion(id='chatcmpl-9Mz7Y3fzo3e42KxG3iFy14i5wiITf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card issue", "card retention", "ATM card retrieval"]', role='assistant', function_call=None, tool_calls=None))], created=1715265192, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["ATM card issue", "card retention", "ATM card retrieval"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I get my card out of the damn ATM?"

Keyphrases:
1930it [1:06:04,  1.74s/it]
ChatCompletion(id='chatcmpl-9Mz7Z98hwEuhOJAyGyYl9J755yasb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card retrieval", "stuck card", "card issue at ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265193, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["ATM card retrieval", "stuck card", "card issue at ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The atm won't give my card back!"

Keyphrases:
1931it [1:06:06,  1.84s/it]
ChatCompletion(id='chatcmpl-9Mz7bNitcccvjNRPViclH8PvGjqJE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card retrieval", "card stuck in ATM", "ATM issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715265195, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=227, total_tokens=244))
["ATM card retrieval", "card stuck in ATM", "ATM issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I get my card back out?"

Keyphrases:
1932it [1:06:08,  1.90s/it]
ChatCompletion(id='chatcmpl-9Mz7dwaEfatQ7LHVkXNDQIG6EkRvD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["retrieve card", "stuck card", "card retrieval issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265197, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["retrieve card", "stuck card", "card retrieval issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM machine stole my card."

Keyphrases:
1933it [1:06:10,  1.75s/it]
ChatCompletion(id='chatcmpl-9Mz7fDOIgPMcWqtvKGv70r3ztvPHs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "card retention", "stolen card by ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265199, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["ATM issue", "card retention", "stolen card by ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM at Metro bank on High St. Kensington swallowed my card. How do I get it back?"

Keyphrases:
1934it [1:06:12,  1.76s/it]
ChatCompletion(id='chatcmpl-9Mz7gtlrV4bXA6NILWezEVsrPZbNx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card retrieval", "card swallowed by ATM", "recover card from ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265200, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=239, total_tokens=257))
["ATM card retrieval", "card swallowed by ATM", "recover card from ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My ATM got stuck and I'm not sure what to do."

Keyphrases:
1935it [1:06:13,  1.69s/it]
ChatCompletion(id='chatcmpl-9Mz7ihgdcfeMCF7R28gX3bMLR4lza', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "stuck card", "ATM malfunction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265202, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["ATM issue", "stuck card", "ATM malfunction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM ate my card."

Keyphrases:
1936it [1:06:14,  1.58s/it]
ChatCompletion(id='chatcmpl-9Mz7jaMh2XnDVJlCZrNipBICcm6K4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card issue", "card retention", "ATM malfunction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265203, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["ATM card issue", "card retention", "ATM malfunction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM won't give me my card back."

Keyphrases:
1937it [1:06:16,  1.60s/it]
ChatCompletion(id='chatcmpl-9Mz7lIwnCaYvHBySlo5kDl8BICtuq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card issue", "card retention", "ATM malfunction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265205, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["ATM card issue", "card retention", "ATM malfunction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card was confiscated by an ATM. How do I get my card back?"

Keyphrases:
1938it [1:06:17,  1.46s/it]
ChatCompletion(id='chatcmpl-9Mz7mhqy5kBFq1bypKJOzIk8wFWLY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card retrieval", "ATM confiscated card", "recover card"]', role='assistant', function_call=None, tool_calls=None))], created=1715265206, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["card retrieval", "ATM confiscated card", "recover card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do if the ATM ate my card?"

Keyphrases:
1939it [1:06:19,  1.60s/it]
ChatCompletion(id='chatcmpl-9Mz7nnRBJuRpTgqi9N5UlPfj3uA1P', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card issue", "card retrieval", "stuck card"]', role='assistant', function_call=None, tool_calls=None))], created=1715265207, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["ATM card issue", "card retrieval", "stuck card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "ATM still has my card"

Keyphrases:
1940it [1:06:22,  1.89s/it]
ChatCompletion(id='chatcmpl-9Mz7pxaaM9dqylnoj2TagjhjdmqH9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card retention", "ATM card issue", "stuck card"]', role='assistant', function_call=None, tool_calls=None))], created=1715265209, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["card retention", "ATM card issue", "stuck card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do if an ATM ate my card?"

Keyphrases:
1941it [1:06:24,  1.94s/it]
ChatCompletion(id='chatcmpl-9Mz7siiVgScwwQZT7i64CPOwmNpCm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card retrieval", "card stuck in ATM", "lost card at ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265212, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=229, total_tokens=247))
["ATM card retrieval", "card stuck in ATM", "lost card at ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What happens if the ATM doesn't give me back my card?"

Keyphrases:
1942it [1:06:25,  1.85s/it]
ChatCompletion(id='chatcmpl-9Mz7urreSFI3XoQuwmqOAnq6dy5Ou', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card retrieval", "card stuck in ATM", "ATM issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715265214, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["ATM card retrieval", "card stuck in ATM", "ATM issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't pull my card out of the ATM. Help me."

Keyphrases:
1943it [1:06:27,  1.76s/it]
ChatCompletion(id='chatcmpl-9Mz7wk6bEEusi9yo2pE0LR0BAdTJb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "card stuck", "ATM assistance"]', role='assistant', function_call=None, tool_calls=None))], created=1715265216, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["ATM issue", "card stuck", "ATM assistance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a problem!  The ATM stole my card!"

Keyphrases:
1944it [1:06:29,  1.75s/it]
ChatCompletion(id='chatcmpl-9Mz7x0AAaphKyRtg5igae67vroyKb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card issue", "card retention", "stolen card by ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265217, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["ATM card issue", "card retention", "stolen card by ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why would an ATM swallow my card?"

Keyphrases:
1945it [1:06:30,  1.65s/it]
ChatCompletion(id='chatcmpl-9Mz7zyIbHcKbdtajpoXGBtqbUoIZy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "card retention", "ATM swallowed card"]', role='assistant', function_call=None, tool_calls=None))], created=1715265219, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["ATM issue", "card retention", "ATM swallowed card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card was taken by the ATM."

Keyphrases:
1946it [1:06:32,  1.65s/it]
ChatCompletion(id='chatcmpl-9Mz80LRxJmY5T9fsF621slH1itAGG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card retrieval", "card captured", "card at ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265220, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["ATM card retrieval", "card captured", "card at ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help!  The atm won't give me my card back."

Keyphrases:
1947it [1:06:33,  1.65s/it]
ChatCompletion(id='chatcmpl-9Mz82NoSSxQEnmWSbiZUQVEuzcDlQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "card retention", "ATM card retrieval"]', role='assistant', function_call=None, tool_calls=None))], created=1715265222, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["ATM issue", "card retention", "ATM card retrieval"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The stupid machine just swallowed my card!! I need a new one ASAP"

Keyphrases:
1948it [1:06:36,  2.07s/it]
ChatCompletion(id='chatcmpl-9Mz84G4pVnO8Ts6BerIuXbRwhrDay', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card swallowed", "issue new card", "ATM card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265224, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["card swallowed", "issue new card", "ATM card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I retrieve a trapped card from a ATM?"

Keyphrases:
1949it [1:06:38,  1.89s/it]
ChatCompletion(id='chatcmpl-9Mz87hShkuZkt9Bb6L5pryhU050lP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["trapped card", "ATM card retrieval", "stuck card help"]', role='assistant', function_call=None, tool_calls=None))], created=1715265227, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["trapped card", "ATM card retrieval", "stuck card help"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is stuck in the ATM, what can I do?"

Keyphrases:
1950it [1:06:40,  1.90s/it]
ChatCompletion(id='chatcmpl-9Mz88uqAa3ou8dKwZPjzYNymUKgKL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card retrieval", "ATM issue", "stuck card"]', role='assistant', function_call=None, tool_calls=None))], created=1715265228, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["card retrieval", "ATM issue", "stuck card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was getting cash and can't get my card back."

Keyphrases:
1951it [1:06:43,  2.28s/it]
ChatCompletion(id='chatcmpl-9Mz8AfLuGleOl5j39TgnYyvfDxgaY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card retrieval", "ATM card stuck", "withdrawal issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265230, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["card retrieval", "ATM card stuck", "withdrawal issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If my card is trapped in the ATM, what do I do?"

Keyphrases:
1952it [1:06:44,  1.98s/it]
ChatCompletion(id='chatcmpl-9Mz8D6FBGE5diAA8d6ZcXD3BpjaQb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card retrieval", "trapped card", "card stuck in ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265233, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=232, total_tokens=249))
["ATM card retrieval", "trapped card", "card stuck in ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card has been swallowed by an ATM"

Keyphrases:
1953it [1:06:46,  1.90s/it]
ChatCompletion(id='chatcmpl-9Mz8FXl1RpKRIfht7k3SGoUhw34JV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card retrieval", "swallowed card", "ATM card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265235, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["card retrieval", "swallowed card", "ATM card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was taking out funds and was unable to regain my card."

Keyphrases:
1954it [1:06:49,  2.19s/it]
ChatCompletion(id='chatcmpl-9Mz8GtmcIwDgP0TSpQY9xYmjBEswE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card retrieval", "ATM issues", "lost card at ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265236, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["card retrieval", "ATM issues", "lost card at ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What should I do with my atm that got stuck?"

Keyphrases:
1955it [1:06:51,  2.02s/it]
ChatCompletion(id='chatcmpl-9Mz8J7O4DbAdC86saA08FnWt1VSTp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "stuck card", "ATM malfunction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265239, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["ATM issue", "stuck card", "ATM malfunction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM at Metro bank on High St. Kensington didn't return my card. What should I do now that the bank is closed?"

Keyphrases:
1956it [1:06:53,  2.12s/it]
ChatCompletion(id='chatcmpl-9Mz8LcWvmZaMd06z0D56nXqkUNUqn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM card retention", "card stuck in ATM", "bank closed help"]', role='assistant', function_call=None, tool_calls=None))], created=1715265241, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=245, total_tokens=262))
["ATM card retention", "card stuck in ATM", "bank closed help"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The ATM won't give back my card"

Keyphrases:
1957it [1:06:55,  2.09s/it]
ChatCompletion(id='chatcmpl-9Mz8OBhMysVjweCkoUpf7fL1TmZfw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "card retention", "card stuck in ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265244, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["ATM issue", "card retention", "card stuck in ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was at an ATM and it swallowed my card."

Keyphrases:
1958it [1:06:57,  1.96s/it]
ChatCompletion(id='chatcmpl-9Mz8PWFMZKc1dWcI9fpYyExFzuxU1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "card retrieval", "swallowed card"]', role='assistant', function_call=None, tool_calls=None))], created=1715265245, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["ATM issue", "card retrieval", "swallowed card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "WTF??? I tried to withdraw some money at a Metro bank on High St. Kensington and without any notice it disappeared in the machine. The bank was already closed so I couldn't do anything. How do I get it back?"

Keyphrases:
1959it [1:06:59,  2.17s/it]
ChatCompletion(id='chatcmpl-9Mz8RHxDV7I5waQ7SvRIeuaGxRzsE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM issue", "withdrawal problem", "money stuck in ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265247, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=265, total_tokens=281))
["ATM issue", "withdrawal problem", "money stuck in ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What happens if my card is stuck in the ATM?"

Keyphrases:
1960it [1:07:01,  1.98s/it]
ChatCompletion(id='chatcmpl-9Mz8TWwL2vkj0SzzKuKyDwKREqCuh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card retrieval", "ATM issues", "stuck card"]', role='assistant', function_call=None, tool_calls=None))], created=1715265249, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["card retrieval", "ATM issues", "stuck card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got double charged for a payment so how do I fix that?"

Keyphrases:
1961it [1:07:02,  1.86s/it]
ChatCompletion(id='chatcmpl-9Mz8Vf9LSNuGF0rCrYdZZswOLLwbA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "rectify payment error", "refund process"]', role='assistant', function_call=None, tool_calls=None))], created=1715265251, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["double charge", "rectify payment error", "refund process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've just come back from an eating holiday in the USA and Canada and have SO many pending and duplicated transactions on my account.  I think there is something wrong, can you look in to it please?"

Keyphrases:
1962it [1:07:07,  2.86s/it]
ChatCompletion(id='chatcmpl-9Mz8XQx451WYKdtNtUoF4aeQGj0BY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transactions", "duplicate transactions", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265253, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=260, total_tokens=272))
["pending transactions", "duplicate transactions", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why am I being charged twice fro a restaurant?"

Keyphrases:
1963it [1:07:09,  2.34s/it]
ChatCompletion(id='chatcmpl-9Mz8czwBWLr60Mr0OySWO6Qg0gIvt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "billing error", "duplicate transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265258, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["double charge", "billing error", "duplicate transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to know why I was charged twice for my purchase."

Keyphrases:
1964it [1:07:11,  2.26s/it]
ChatCompletion(id='chatcmpl-9Mz8dpIPBz3XYlRNlINQmofWInMI4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "incorrect billing", "duplicate transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265259, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["double charge", "incorrect billing", "duplicate transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I didn't buy this twice"

Keyphrases:
1965it [1:07:13,  2.25s/it]
ChatCompletion(id='chatcmpl-9Mz8fpsvmxcFuKGmeBBkfcmgqfATh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate transaction", "unauthorized charge", "reverse payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715265261, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["duplicate transaction", "unauthorized charge", "reverse payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I chaged twice for the same thing?"

Keyphrases:
1966it [1:07:17,  2.86s/it]
ChatCompletion(id='chatcmpl-9Mz8h07AyOy2PwsMuFBuZPXXXcoTF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charging", "overcharge", "billing error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265263, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["double charging", "overcharge", "billing error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is there more then one charge on my card I only paid for one not twice how can I fix this?"

Keyphrases:
1967it [1:07:19,  2.47s/it]
ChatCompletion(id='chatcmpl-9Mz8lG24kxp2jzKOpQ2J4O10uqCFu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate charge", "unauthorized charge", "billing issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265267, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=241, total_tokens=254))
["duplicate charge", "unauthorized charge", "billing issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a duplicate payment showing up on the app. How do I stop myself being charged for the thing twice?"

Keyphrases:
1968it [1:07:20,  2.09s/it]
ChatCompletion(id='chatcmpl-9Mz8nrkZC1hBMJq9h08EXAK7TorZq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate payment", "charge dispute", "prevent double charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715265269, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=241, total_tokens=254))
["duplicate payment", "charge dispute", "prevent double charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why would I be charged more than once for the same transaction?"

Keyphrases:
1969it [1:07:22,  1.99s/it]
ChatCompletion(id='chatcmpl-9Mz8oEbtCri2Fl3taM5lJ50FHyXrP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate charges", "multiple transaction charges", "overcharge issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265270, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["duplicate charges", "multiple transaction charges", "overcharge issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was wondering how I could have two charges for the same item happen more than once in a 7 day period. Is there anyway I could get this corrected asap."

Keyphrases:
1970it [1:07:23,  1.76s/it]
ChatCompletion(id='chatcmpl-9Mz8q4PvwNGFBXxuiEI8Y7whJw5oR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate charges", "billing error", "charge correction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265272, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=253, total_tokens=265))
["duplicate charges", "billing error", "charge correction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you please check if I was charged twice?"

Keyphrases:
1971it [1:07:25,  1.79s/it]
ChatCompletion(id='chatcmpl-9Mz8rvjvCV2DGwkaUwoClMZu6ouZa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "duplicate transaction", "check payment status"]', role='assistant', function_call=None, tool_calls=None))], created=1715265273, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["double charge", "duplicate transaction", "check payment status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have been charged twice"

Keyphrases:
1972it [1:07:26,  1.65s/it]
ChatCompletion(id='chatcmpl-9Mz8tbfxYKE29yzC0ZfhNIJrg9KXd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "refund request", "billing issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265275, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["double charge", "refund request", "billing issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It appears that I am being double charged for some items that I have purchased this past week.  Please review and correct."

Keyphrases:
1973it [1:07:28,  1.81s/it]
ChatCompletion(id='chatcmpl-9Mz8uDldE6e4UXJ6dwnn8CxKe4Zb2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charging", "billing error", "transaction review"]', role='assistant', function_call=None, tool_calls=None))], created=1715265276, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=243, total_tokens=255))
["double charging", "billing error", "transaction review"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It looks like this week I was double charged for a couple things. Is there any way that you can look into this for me and return the double charged items back to my card?"

Keyphrases:
1974it [1:07:30,  1.78s/it]
ChatCompletion(id='chatcmpl-9Mz8xIaRzhhCpCRYduvNfE4nVUAxj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "refund request", "transaction review"]', role='assistant', function_call=None, tool_calls=None))], created=1715265279, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=255, total_tokens=267))
["double charge", "refund request", "transaction review"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I noticed after looking over my transactions that I have been charged twice from an earlier restaurant visit this week. Is it possible that one of these can be removed so I get the money back for the one that is not accurate?"

Keyphrases:
1975it [1:07:32,  1.89s/it]
ChatCompletion(id='chatcmpl-9Mz8zuWy4dfHCICODsfXRDDeXBb9B', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "refund request", "transaction dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715265281, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=263, total_tokens=275))
["double charge", "refund request", "transaction dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think something may have happened that caused a charge to show up twice."

Keyphrases:
1976it [1:07:35,  2.22s/it]
ChatCompletion(id='chatcmpl-9Mz90G6Yq4c6xCFSgkO12wJB99CUT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate charge", "charge dispute", "billing error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265282, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=233, total_tokens=245))
["duplicate charge", "charge dispute", "billing error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is there a transaction that shows multiple times?"

Keyphrases:
1977it [1:07:37,  1.98s/it]
ChatCompletion(id='chatcmpl-9Mz93oc2b7LLTTW8g5kBw2Zp6THL7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate transaction", "repeated charge", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265285, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["duplicate transaction", "repeated charge", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I see what looks like duplicate charges on account."

Keyphrases:
1978it [1:07:38,  1.81s/it]
ChatCompletion(id='chatcmpl-9Mz95834V7fMe7G3HgarXog93qK2M', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate charges", "account discrepancy", "double billing"]', role='assistant', function_call=None, tool_calls=None))], created=1715265287, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["duplicate charges", "account discrepancy", "double billing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I charged multiple times for the same thing?"

Keyphrases:
1979it [1:07:39,  1.64s/it]
ChatCompletion(id='chatcmpl-9Mz961bLMUzn2cnBAXGUIPvQXJ98O', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple charges", "billing error", "duplicate transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265288, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["multiple charges", "billing error", "duplicate transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I had a duplicate card and got charged twice. How do I resolve this?"

Keyphrases:
1980it [1:07:41,  1.64s/it]
ChatCompletion(id='chatcmpl-9Mz98FTgw8a29WWKhCaW9zBOMvPtA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate charge", "card issue", "charge dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715265290, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=234, total_tokens=246))
["duplicate charge", "card issue", "charge dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hello. I checked my transactions and saw I was double charged on my card for a restaurant visit. I would like to get my money back."

Keyphrases:
1981it [1:07:43,  1.82s/it]
ChatCompletion(id='chatcmpl-9Mz99wMWk7UqurZguhBKdfXhecro7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "refund request", "transaction dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715265291, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=247, total_tokens=259))
["double charge", "refund request", "transaction dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why am I being charged twice?"

Keyphrases:
1982it [1:07:45,  1.83s/it]
ChatCompletion(id='chatcmpl-9Mz9BfUsHUFe21QEWxhmcuuDLsX0W', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate charge", "double billing", "billing error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265293, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["duplicate charge", "double billing", "billing error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Transactions on my card look really weird. I've been charged twice for a couple things this week! Please check this and return the double charged ones."

Keyphrases:
1983it [1:07:48,  2.11s/it]
ChatCompletion(id='chatcmpl-9Mz9D6vP5OB18im175or66dGiXnHa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "fraudulent transactions", "transaction dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715265295, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=248, total_tokens=262))
["double charge", "fraudulent transactions", "transaction dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please check payments on my card. There is a duplicate and I only bought it once."

Keyphrases:
1984it [1:07:49,  1.87s/it]
ChatCompletion(id='chatcmpl-9Mz9GbWihrqqvBlFAoSFEuCiBFyFZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate payment", "check payments", "payment error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265298, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=236, total_tokens=248))
["duplicate payment", "check payments", "payment error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "More than one time this week, I have been charged more than once for the same transaction. Please correct the issue and refund the duplicate charges."

Keyphrases:
1985it [1:07:50,  1.70s/it]
ChatCompletion(id='chatcmpl-9Mz9HyruuXxnaYkLe4Ex6fpw7YOHq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate charges", "refund request", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265299, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=247, total_tokens=259))
["duplicate charges", "refund request", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "A transaction is repeated several times on my account."

Keyphrases:
1986it [1:07:52,  1.66s/it]
ChatCompletion(id='chatcmpl-9Mz9JBcoUkperLswIyBZHKSjtBFIY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate transaction", "repeated charges", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265301, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["duplicate transaction", "repeated charges", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've been charged more than once for the same transaction"

Keyphrases:
1987it [1:07:54,  1.72s/it]
ChatCompletion(id='chatcmpl-9Mz9LozJ0hrKYLV6rAU9yGYmvJ46r', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate charge", "multiple charges", "billing error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265303, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["duplicate charge", "multiple charges", "billing error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card has been charged two separate times for a single transaction."

Keyphrases:
1988it [1:07:55,  1.56s/it]
ChatCompletion(id='chatcmpl-9Mz9MOa1ircyDNXhKjEIbG1fx90bA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "incorrect billing", "transaction dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715265304, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["double charge", "incorrect billing", "transaction dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you explain why there is a payment showing twice?"

Keyphrases:
1989it [1:07:57,  1.56s/it]
ChatCompletion(id='chatcmpl-9Mz9NaumOhGsdLx2xidkWPqJiS5D8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate payment", "payment error", "double charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715265305, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["duplicate payment", "payment error", "double charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why have I been charged twice for the same transaction?"

Keyphrases:
1990it [1:07:58,  1.43s/it]
ChatCompletion(id='chatcmpl-9Mz9Pp2Pz1Mq2jGkCW5sH44unYX0P', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate charge", "double billing", "payment error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265307, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["duplicate charge", "double billing", "payment error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I see that I have been charged multiple times for the same transaction."

Keyphrases:
1991it [1:08:00,  1.68s/it]
ChatCompletion(id='chatcmpl-9Mz9QjKJrlb9xQuXkktCEEUYgEl6S', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple charges", "duplicate transaction", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265308, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["multiple charges", "duplicate transaction", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was double charged"

Keyphrases:
1992it [1:08:02,  1.67s/it]
ChatCompletion(id='chatcmpl-9Mz9Sk9zvt0mliwN7V2s90LOJIRtO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "overcharge", "billing error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265310, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["double charge", "overcharge", "billing error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have multiple charges on the same transaction."

Keyphrases:
1993it [1:08:04,  2.03s/it]
ChatCompletion(id='chatcmpl-9Mz9VlyY7pOCIgYCgSBYHxa61rPYS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate charges", "transaction error", "multiple billing"]', role='assistant', function_call=None, tool_calls=None))], created=1715265313, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["duplicate charges", "transaction error", "multiple billing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Looks like my card payment was duplicated. I went to pay at the store earlier, got declined once,second time it works. App still stays pending for one of the payments. Can you please remove one of them as it's wrong and clearly was declined?"

Keyphrases:
1994it [1:08:06,  1.82s/it]
ChatCompletion(id='chatcmpl-9Mz9X2EER5yhZSsXIkMEdnxwRWbNn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate payment", "resolve duplicate charge", "cancel pending transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265315, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=270, total_tokens=284))
["duplicate payment", "resolve duplicate charge", "cancel pending transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a transaction that shows several times"

Keyphrases:
1995it [1:08:07,  1.61s/it]
ChatCompletion(id='chatcmpl-9Mz9YEGhpM53GOsTTGQExyzACTJo0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate transaction", "repeated charge", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265316, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["duplicate transaction", "repeated charge", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I recently got charged twice from a restaurant that I was at this week and I would like for one of those payments to be removed from my account."

Keyphrases:
1996it [1:08:09,  1.86s/it]
ChatCompletion(id='chatcmpl-9Mz9ZH1q2yk1ZbhKe459wDLSvM4M9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "incorrect charge", "payment dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715265317, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=248, total_tokens=260))
["double charge", "incorrect charge", "payment dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is more than one of the same transaction on my account."

Keyphrases:
1997it [1:08:11,  1.79s/it]
ChatCompletion(id='chatcmpl-9Mz9ciwZirK8cHkcN3F3wNFYzsao2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate transaction", "multiple charges", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265320, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["duplicate transaction", "multiple charges", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a duplicate payment showing"

Keyphrases:
1998it [1:08:12,  1.64s/it]
ChatCompletion(id='chatcmpl-9Mz9dAvakKkH7tzUAteifDNL6qnZe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate payment", "payment error", "double charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715265321, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["duplicate payment", "payment error", "double charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a payment that got charged twice instead of once."

Keyphrases:
1999it [1:08:14,  1.62s/it]
ChatCompletion(id='chatcmpl-9Mz9flGZFg0Soc81TT4o9NYb6Reer', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["duplicate payment", "overcharged", "payment error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265323, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["duplicate payment", "overcharged", "payment error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are my remedies if I think I was charged twice for the same expense?"

Keyphrases:
2000it [1:08:17,  1.94s/it]
ChatCompletion(id='chatcmpl-9Mz9h82YAh6KrvRtkDsQ0HqjXoqUj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["double charge", "dispute transaction", "billing error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265325, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["double charge", "dispute transaction", "billing error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I verify the source of my funds?"

Keyphrases:
2001it [1:08:18,  1.88s/it]
ChatCompletion(id='chatcmpl-9Mz9jr7AmQk9vIqa78WDCmsBxKUz8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund source verification", "verify fund origin", "source of funds check"]', role='assistant', function_call=None, tool_calls=None))], created=1715265327, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["fund source verification", "verify fund origin", "source of funds check"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want information about the source of funds."

Keyphrases:
2002it [1:08:20,  1.91s/it]
ChatCompletion(id='chatcmpl-9Mz9lvH6ljY1lxezP3sQ0CZ6yjs2c', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "fund origin", "financial source information"]', role='assistant', function_call=None, tool_calls=None))], created=1715265329, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["source of funds", "fund origin", "financial source information"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where are my funds being sourced from?"

Keyphrases:
2003it [1:08:22,  1.76s/it]
ChatCompletion(id='chatcmpl-9Mz9nWouj2XNi9yfKpPt1xhcz9HG9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund source", "funding details", "payment origin"]', role='assistant', function_call=None, tool_calls=None))], created=1715265331, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["fund source", "funding details", "payment origin"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to verify the source of my money"

Keyphrases:
2004it [1:08:23,  1.67s/it]
ChatCompletion(id='chatcmpl-9Mz9ofFUawg6tM6GIdfKchpycBMmX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money source verification", "verify funds origin", "source of income verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715265332, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["money source verification", "verify funds origin", "source of income verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "where to funds come from"

Keyphrases:
2005it [1:08:24,  1.50s/it]
ChatCompletion(id='chatcmpl-9Mz9p9uYb8ASghCYp6fNYNk9Mr1Yk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "funds origin", "transfer source"]', role='assistant', function_call=None, tool_calls=None))], created=1715265333, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["source of funds", "funds origin", "transfer source"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the source of my funds."

Keyphrases:
2006it [1:08:28,  2.09s/it]
ChatCompletion(id='chatcmpl-9Mz9qYJMbJD4wgnDMN9wU2P3ZNpkl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund origin", "source of funds", "fund source"]', role='assistant', function_call=None, tool_calls=None))], created=1715265334, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["fund origin", "source of funds", "fund source"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to verify my source of funds"

Keyphrases:
2007it [1:08:30,  2.02s/it]
ChatCompletion(id='chatcmpl-9Mz9uio2lmEwCVWkSyTJ8gZbDcqUE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds verification", "verify funds", "funds origin check"]', role='assistant', function_call=None, tool_calls=None))], created=1715265338, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["source of funds verification", "verify funds", "funds origin check"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to see the source of my money."

Keyphrases:
2008it [1:08:31,  1.90s/it]
ChatCompletion(id='chatcmpl-9Mz9w2khqoaJXbyLt8oLO5SdEnFG0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "origin of money", "money source tracking"]', role='assistant', function_call=None, tool_calls=None))], created=1715265340, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["source of funds", "origin of money", "money source tracking"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do you need all this information about my Source of Funds?"

Keyphrases:
2009it [1:08:33,  1.81s/it]
ChatCompletion(id='chatcmpl-9Mz9xztiHRIHo84xgslZZWMNFSb01', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "documentation requirement", "compliance query"]', role='assistant', function_call=None, tool_calls=None))], created=1715265341, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["source of funds", "documentation requirement", "compliance query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I check the source of funds?"

Keyphrases:
2010it [1:08:35,  1.92s/it]
ChatCompletion(id='chatcmpl-9Mz9zX5NO4hEb1r97zfab0BBMrjdY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "fund origin", "verify funds source"]', role='assistant', function_call=None, tool_calls=None))], created=1715265343, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["source of funds", "fund origin", "verify funds source"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I tell where my funds came from?"

Keyphrases:
2011it [1:08:42,  3.47s/it]
ChatCompletion(id='chatcmpl-9MzA12MEcSzIFJRGTMEzF3rf7kylJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "funds origin", "track fund source"]', role='assistant', function_call=None, tool_calls=None))], created=1715265345, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["source of funds", "funds origin", "track fund source"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the source of my available funds?"

Keyphrases:
2012it [1:08:44,  3.07s/it]
ChatCompletion(id='chatcmpl-9MzA8Zhexd0TlmUX0SjfIkpIrGFBh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund source", "available balance origin", "source of funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715265352, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["fund source", "available balance origin", "source of funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I find the origination of my funds?"

Keyphrases:
2013it [1:08:46,  2.64s/it]
ChatCompletion(id='chatcmpl-9MzAAUIC6c6VztH80bV5yYVlk73R8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund origination", "source of funds", "track funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715265354, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["fund origination", "source of funds", "track funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My source of funds need verified."

Keyphrases:
2014it [1:08:48,  2.46s/it]
ChatCompletion(id='chatcmpl-9MzAC1FwKp2iCRG5kSpFjoS50jL6P', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source verification", "funds verification", "verify source of funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715265356, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["source verification", "funds verification", "verify source of funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What information do you need to verify my Source of Funds?"

Keyphrases:
2015it [1:08:49,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzAEm58Z2txV7tEneD5DU3kboGhW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds verification", "verification requirements", "documentation for funds verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715265358, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["source of funds verification", "verification requirements", "documentation for funds verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need the source of my funds verified. How do I do this?"

Keyphrases:
2016it [1:08:52,  2.22s/it]
ChatCompletion(id='chatcmpl-9MzAGBitSXvwDiJ9R9rUT0NPXAZkH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund source verification", "verify source of funds", "source verification process"]', role='assistant', function_call=None, tool_calls=None))], created=1715265360, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["fund source verification", "verify source of funds", "source verification process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need my funds verified."

Keyphrases:
2017it [1:08:54,  2.26s/it]
ChatCompletion(id='chatcmpl-9MzAIp74sip14rVyS1TT40tJU1qoi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund verification", "verify funds", "account verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715265362, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["fund verification", "verify funds", "account verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help me check where the funds came from."

Keyphrases:
2018it [1:08:55,  2.03s/it]
ChatCompletion(id='chatcmpl-9MzAKhuybCtnQAeXFtojghwaKLO6x', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "transaction origin", "funds received"]', role='assistant', function_call=None, tool_calls=None))], created=1715265364, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["source of funds", "transaction origin", "funds received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to know where the funds come from."

Keyphrases:
2019it [1:08:58,  2.07s/it]
ChatCompletion(id='chatcmpl-9MzAMdkvUmHm5hHSBrVqa4So6a2at', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund origin", "source of funds", "fund source inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715265366, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["fund origin", "source of funds", "fund source inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the source of my money?"

Keyphrases:
2020it [1:09:01,  2.35s/it]
ChatCompletion(id='chatcmpl-9MzAO8lnYGXqjM66VOrUlJXBnL1Jz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "money origin", "transaction source"]', role='assistant', function_call=None, tool_calls=None))], created=1715265368, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["source of funds", "money origin", "transaction source"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I find the source of my available money?"

Keyphrases:
2021it [1:09:02,  2.07s/it]
ChatCompletion(id='chatcmpl-9MzARXtwYKcpwOWVstqR4svBGZjBy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "available balance origin", "money source"]', role='assistant', function_call=None, tool_calls=None))], created=1715265371, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["source of funds", "available balance origin", "money source"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I lookup where funds came from?"

Keyphrases:
2022it [1:09:05,  2.29s/it]
ChatCompletion(id='chatcmpl-9MzASpVTStH2eDO3X9IAS3l9ICXyR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "fund origin", "trace funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715265372, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["source of funds", "fund origin", "trace funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I see that history on my funds and where they came from?"

Keyphrases:
2023it [1:09:08,  2.55s/it]
ChatCompletion(id='chatcmpl-9MzAVsMv1v5ZnI8yOOU8rvqgGGNif', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["funds history", "transaction sources", "account history"]', role='assistant', function_call=None, tool_calls=None))], created=1715265375, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["funds history", "transaction sources", "account history"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have to verify the source of my funds"

Keyphrases:
2024it [1:09:10,  2.24s/it]
ChatCompletion(id='chatcmpl-9MzAYdzlfWQK9oVi9CR0sMa2ar2fo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund source verification", "verify financial source", "source of income check"]', role='assistant', function_call=None, tool_calls=None))], created=1715265378, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["fund source verification", "verify financial source", "source of income check"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I view the source of my available funds?"

Keyphrases:
2025it [1:09:11,  2.03s/it]
ChatCompletion(id='chatcmpl-9MzAavzH7BcMg6mScVvADVBmr2C7N', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "view available funds", "fund origins"]', role='assistant', function_call=None, tool_calls=None))], created=1715265380, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["source of funds", "view available funds", "fund origins"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why does my money come from?"

Keyphrases:
2026it [1:09:13,  1.96s/it]
ChatCompletion(id='chatcmpl-9MzAbSk8gdwLvHvHVLI4mtuQViRsy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "money origin", "fund source"]', role='assistant', function_call=None, tool_calls=None))], created=1715265381, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["source of funds", "money origin", "fund source"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to validate the source of my funds."

Keyphrases:
2027it [1:09:17,  2.52s/it]
ChatCompletion(id='chatcmpl-9MzAdmL12MRXLWg8bF7n3Ab189WGw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund source validation", "source of funds", "validate financial source"]', role='assistant', function_call=None, tool_calls=None))], created=1715265383, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["fund source validation", "source of funds", "validate financial source"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where are my funds coming from? I need to know."

Keyphrases:
2028it [1:09:19,  2.32s/it]
ChatCompletion(id='chatcmpl-9MzAhRLETQBP446kMI1R7jkAhBLF8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "fund origin", "transaction details"]', role='assistant', function_call=None, tool_calls=None))], created=1715265387, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["source of funds", "fund origin", "transaction details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where has my available money come from?"

Keyphrases:
2029it [1:09:20,  2.09s/it]
ChatCompletion(id='chatcmpl-9MzAjhRYsuSHvHYC8TXdX1kquEq5l', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "money origin", "account credits"]', role='assistant', function_call=None, tool_calls=None))], created=1715265389, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["source of funds", "money origin", "account credits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do you need to know where my money is coming from?"

Keyphrases:
2030it [1:09:22,  2.11s/it]
ChatCompletion(id='chatcmpl-9MzAlIOGVHZdbMxDA6oqL6xNegFNP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "money origin verification", "compliance query"]', role='assistant', function_call=None, tool_calls=None))], created=1715265391, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["source of funds", "money origin verification", "compliance query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I see where my money comes from?"

Keyphrases:
2031it [1:09:24,  1.89s/it]
ChatCompletion(id='chatcmpl-9MzAmiSrwyN5GMQavkELJ7Pq5ZVJE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money source", "transaction origin", "funds origin"]', role='assistant', function_call=None, tool_calls=None))], created=1715265392, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["money source", "transaction origin", "funds origin"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I check the source for my funds?"

Keyphrases:
2032it [1:09:26,  1.98s/it]
ChatCompletion(id='chatcmpl-9MzAoEgpFvL4VmFsWMtLUeZhppkY3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund source", "check fund origin", "transaction details"]', role='assistant', function_call=None, tool_calls=None))], created=1715265394, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["fund source", "check fund origin", "transaction details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I see the source of my money?"

Keyphrases:
2033it [1:09:29,  2.42s/it]
ChatCompletion(id='chatcmpl-9MzAsDNeXZXPys9Rx1X8pFhYPX5ay', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money source", "funds origin", "transaction details"]', role='assistant', function_call=None, tool_calls=None))], created=1715265398, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["money source", "funds origin", "transaction details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what is source of my funds, need to verify"

Keyphrases:
2034it [1:09:31,  2.17s/it]
ChatCompletion(id='chatcmpl-9MzAuGdIBOTYcaFjAe5XtTR3XLzcB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund source", "verify funds", "origin of funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715265400, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["fund source", "verify funds", "origin of funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do my funds come from?"

Keyphrases:
2035it [1:09:32,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzAv8ubsm4Tj2F2Wbc0XnZHwaTcv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "fund origin", "money source"]', role='assistant', function_call=None, tool_calls=None))], created=1715265401, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["source of funds", "fund origin", "money source"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I check the source of my fund?"

Keyphrases:
2036it [1:09:34,  1.77s/it]
ChatCompletion(id='chatcmpl-9MzAw4fDjAnpVzGYxJ1U1yFgsswV1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund source", "origin of funds", "trace funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715265402, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["fund source", "origin of funds", "trace funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I see my source of funds?"

Keyphrases:
2037it [1:09:35,  1.67s/it]
ChatCompletion(id='chatcmpl-9MzAyBbyg3HNeiOKTT1WYQAMtOR3h', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "funds origin", "view funding sources"]', role='assistant', function_call=None, tool_calls=None))], created=1715265404, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["source of funds", "funds origin", "view funding sources"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I become aware of where my funds come from?"

Keyphrases:
2038it [1:09:37,  1.63s/it]
ChatCompletion(id='chatcmpl-9MzAz9gU0M1KQZjbz731Ak4aNieOg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund source", "origin of funds", "track fund source"]', role='assistant', function_call=None, tool_calls=None))], created=1715265405, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["fund source", "origin of funds", "track fund source"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where does all this money come from though?"

Keyphrases:
2039it [1:09:38,  1.57s/it]
ChatCompletion(id='chatcmpl-9MzB1kDfom4xu9Nad7JTl7P9hbzf3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["source of funds", "money origin", "fund origin"]', role='assistant', function_call=None, tool_calls=None))], created=1715265407, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["source of funds", "money origin", "fund origin"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I need to do to verify the source of my funds?"

Keyphrases:
2040it [1:09:40,  1.65s/it]
ChatCompletion(id='chatcmpl-9MzB3UCv8qb9bnLynvuaxXpjvIHj4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund source verification", "source of funds", "compliance requirements"]', role='assistant', function_call=None, tool_calls=None))], created=1715265409, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["fund source verification", "source of funds", "compliance requirements"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the number of days I have to wait for my Europe transfer?"

Keyphrases:
2041it [1:09:42,  1.77s/it]
ChatCompletion(id='chatcmpl-9MzB4HRkKj7CBy3mpw3VQ2P4OF93J', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer duration", "Europe transfer waiting time", "transfer ETA"]', role='assistant', function_call=None, tool_calls=None))], created=1715265410, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["transfer duration", "Europe transfer waiting time", "transfer ETA"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the wait time for a transfer from the US?"

Keyphrases:
2042it [1:09:44,  1.79s/it]
ChatCompletion(id='chatcmpl-9MzB6v4vhStRDGKC3aLpdYATNeDR2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer wait time", "international transfer time", "US transfer duration"]', role='assistant', function_call=None, tool_calls=None))], created=1715265412, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["transfer wait time", "international transfer time", "US transfer duration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need a fast transfer from China?  How fast will it be?"

Keyphrases:
2043it [1:09:45,  1.71s/it]
ChatCompletion(id='chatcmpl-9MzB8C0LvhJNNQkCnPj6K19DXrQUV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["speed of transfer", "international transfer speed", "transfer time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265414, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["speed of transfer", "international transfer speed", "transfer time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how soon will I see the transfer in my account?"

Keyphrases:
2044it [1:09:48,  1.98s/it]
ChatCompletion(id='chatcmpl-9MzBACthaRk46cnZtP6xNTvEvIcYg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer status", "transfer timing", "account update"]', role='assistant', function_call=None, tool_calls=None))], created=1715265416, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["transfer status", "transfer timing", "account update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many days does it take until funds are in my account?"

Keyphrases:
2045it [1:09:50,  2.06s/it]
ChatCompletion(id='chatcmpl-9MzBCaOGx4glmHvLJKEdZ5QEyhYJm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer time", "fund availability", "transfer duration"]', role='assistant', function_call=None, tool_calls=None))], created=1715265418, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["fund transfer time", "fund availability", "transfer duration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long until my transfer goes through?"

Keyphrases:
2046it [1:09:52,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzBFW8Xwlk70k5ZPIh1qZqq0Ypdo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer timing", "transfer duration", "transfer processing time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265421, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["transfer timing", "transfer duration", "transfer processing time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do transfers from Europe take longer?"

Keyphrases:
2047it [1:09:54,  1.94s/it]
ChatCompletion(id='chatcmpl-9MzBGmAuGqCXiGkISzKfPcqprl5aH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer duration", "Europe transfers", "international transfer time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265422, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["transfer duration", "Europe transfers", "international transfer time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the fastest that I can make a transfer?"

Keyphrases:
2048it [1:09:56,  1.94s/it]
ChatCompletion(id='chatcmpl-9MzBIjuNPatCBWSLgQa6dDyYGW212', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer speed", "quick transfer", "fastest transfer time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265424, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["transfer speed", "quick transfer", "fastest transfer time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how long dies it take for transfers to reflect on my balance"

Keyphrases:
2049it [1:10:00,  2.53s/it]
ChatCompletion(id='chatcmpl-9MzBK0UpvnUAFGdio7gNYkdbdqxCY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer time", "balance update", "transaction reflection time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265426, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["transfer time", "balance update", "transaction reflection time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I started the Bank transfer from Europe, how long will the process take to complete?"

Keyphrases:
2050it [1:10:03,  2.80s/it]
ChatCompletion(id='chatcmpl-9MzBOmFwf0e3KfoAEMIbde5GtGnSY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bank transfer duration", "transfer time", "international transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265430, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=236, total_tokens=249))
["bank transfer duration", "transfer time", "international transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long until the money is in my account?"

Keyphrases:
2051it [1:10:05,  2.62s/it]
ChatCompletion(id='chatcmpl-9MzBSx5gMelAxHCMQMbM4OiQ5eKZE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer time", "money deposit", "transaction completion time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265434, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["fund transfer time", "money deposit", "transaction completion time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will a transfer reach my account?"

Keyphrases:
2052it [1:10:07,  2.32s/it]
ChatCompletion(id='chatcmpl-9MzBULYAfY2LigN3Tp8Qd94xS2AXK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer timing", "expected transfer date", "receiving transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265436, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["transfer timing", "expected transfer date", "receiving transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When should I expect to see my transfer hit my account?"

Keyphrases:
2053it [1:10:11,  2.86s/it]
ChatCompletion(id='chatcmpl-9MzBVV4M0GkpiNiMpciL0Ek388BOh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer timing", "expected transfer date", "transfer receipt"]', role='assistant', function_call=None, tool_calls=None))], created=1715265437, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["transfer timing", "expected transfer date", "transfer receipt"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will my transfer immediately show up in my account?"

Keyphrases:
2054it [1:10:12,  2.36s/it]
ChatCompletion(id='chatcmpl-9MzBZXBGEzLLL2lprF3RT7MKfSSNc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["instant transfer", "transfer visibility", "account update"]', role='assistant', function_call=None, tool_calls=None))], created=1715265441, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["instant transfer", "transfer visibility", "account update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I need to do a quick transfer from China, how long should I expect the transfer to take?"

Keyphrases:
2055it [1:10:14,  2.24s/it]
ChatCompletion(id='chatcmpl-9MzBbBwWcVbGHV5EHq5cTDHAfEEYB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international transfer time", "quick transfer duration", "transfer ETA from China"]', role='assistant', function_call=None, tool_calls=None))], created=1715265443, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=239, total_tokens=255))
["international transfer time", "quick transfer duration", "transfer ETA from China"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When does the money get transferred to my account"

Keyphrases:
2056it [1:10:16,  2.12s/it]
ChatCompletion(id='chatcmpl-9MzBcWPxE4yJ9VbS578IoZ7rUfcKw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer timing", "account deposit schedule", "transfer completion time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265444, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["money transfer timing", "account deposit schedule", "transfer completion time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long do i have to wait for a transfer to reach my account?"

Keyphrases:
2057it [1:10:18,  1.99s/it]
ChatCompletion(id='chatcmpl-9MzBeOwTJLIqq50DT74ivgan8ujmZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer time", "receiving transfer", "transfer delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715265446, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["transfer time", "receiving transfer", "transfer delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does it take for funds to come through the US to my account?"

Keyphrases:
2058it [1:10:20,  2.00s/it]
ChatCompletion(id='chatcmpl-9MzBgJy2NGXPcFGRp91wQMvlsQmqT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["funds transfer time", "international transfer duration", "US to account transfer time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265448, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=234, total_tokens=252))
["funds transfer time", "international transfer duration", "US to account transfer time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long is my Europe transfer wait?"

Keyphrases:
2059it [1:10:21,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzBiRE553dVUvmU9diPqVTkAVuxY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer duration", "Europe transfer time", "wait time for transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265450, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["transfer duration", "Europe transfer time", "wait time for transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many days does a transfer from the US take?"

Keyphrases:
2060it [1:10:22,  1.63s/it]
ChatCompletion(id='chatcmpl-9MzBjQnxmm5rqf0h2TwGuNsiHZhde', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer duration", "US transfer time", "international transfer time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265451, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["transfer duration", "US transfer time", "international transfer time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long do I have to wait for a transfer from the US?"

Keyphrases:
2061it [1:10:24,  1.77s/it]
ChatCompletion(id='chatcmpl-9MzBlbGCPSEnnNJdV8RvUv7JaIHxk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer time", "international transfer duration", "US transfer waiting time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265453, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["transfer time", "international transfer duration", "US transfer waiting time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long is the wait for a US transfer?"

Keyphrases:
2062it [1:10:27,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzBnONoijCguiCaHsK6KvEu6wc3F', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["US transfer time", "transfer duration", "wait time for transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265455, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["US transfer time", "transfer duration", "wait time for transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many days until the money will be in my account?"

Keyphrases:
2063it [1:10:30,  2.26s/it]
ChatCompletion(id='chatcmpl-9MzBpm6dF6uQOsXaYQsTQ7cyOuLrr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer time", "transaction completion", "money receipt time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265457, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["fund transfer time", "transaction completion", "money receipt time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does it take for a transfer?"

Keyphrases:
2064it [1:10:31,  2.10s/it]
ChatCompletion(id='chatcmpl-9MzBsvgCfeVduxCtycFMbuHeSt917', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer duration", "transfer time", "time to complete transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265460, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["transfer duration", "transfer time", "time to complete transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the time frame for a transfer from the US?"

Keyphrases:
2065it [1:10:38,  3.32s/it]
ChatCompletion(id='chatcmpl-9MzBuwXCcRBJz2xUuo8YzEG9evIDQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer time frame", "international transfer duration", "US transfer schedule"]', role='assistant', function_call=None, tool_calls=None))], created=1715265462, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["transfer time frame", "international transfer duration", "US transfer schedule"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "when will i receive a US transfer"

Keyphrases:
2066it [1:10:39,  2.84s/it]
ChatCompletion(id='chatcmpl-9MzC06iPBasJzbsxX58GVvsdkrltL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["US transfer timing", "receiving transfers", "transfer ETA"]', role='assistant', function_call=None, tool_calls=None))], created=1715265468, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["US transfer timing", "receiving transfers", "transfer ETA"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Approximately how long will an urgent transfer from China take?"

Keyphrases:
2067it [1:10:41,  2.45s/it]
ChatCompletion(id='chatcmpl-9MzC2ktbL4Y2YXg1PHbjIt3QTOXm7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["urgent transfer time", "international transfer duration", "transfer ETA"]', role='assistant', function_call=None, tool_calls=None))], created=1715265470, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["urgent transfer time", "international transfer duration", "transfer ETA"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I initiated a Bank transfer form Europe, how long will this take?"

Keyphrases:
2068it [1:10:42,  2.08s/it]
ChatCompletion(id='chatcmpl-9MzC3qobqAaHjCufib24ZfYaADT9T', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international transfer duration", "bank transfer time", "transfer ETA"]', role='assistant', function_call=None, tool_calls=None))], created=1715265471, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["international transfer duration", "bank transfer time", "transfer ETA"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does it take to process transfers from Europe?"

Keyphrases:
2069it [1:10:44,  2.02s/it]
ChatCompletion(id='chatcmpl-9MzC4xSOUvj63xW4eEhLv6P29FYtK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer processing time", "Europe transfer delay", "international transfer duration"]', role='assistant', function_call=None, tool_calls=None))], created=1715265472, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["transfer processing time", "Europe transfer delay", "international transfer duration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does a funds transfer take from one back to another?"

Keyphrases:
2070it [1:10:47,  2.21s/it]
ChatCompletion(id='chatcmpl-9MzC6yQlZVa7OmwvlrDnBQ7TELWwb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["funds transfer time", "interbank transfer duration", "transfer delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715265474, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["funds transfer time", "interbank transfer duration", "transfer delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What would the approximate delivery date be if I transferred something urgently to China?"

Keyphrases:
2071it [1:10:50,  2.40s/it]
ChatCompletion(id='chatcmpl-9MzC9x44fP9QH6Bel4CHlP9AqJwng', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["urgent delivery date", "transfer to China", "expedited shipping"]', role='assistant', function_call=None, tool_calls=None))], created=1715265477, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["urgent delivery date", "transfer to China", "expedited shipping"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have to transfer something to China as fast as I can. How long will it take to arrive in China?"

Keyphrases:
2072it [1:10:52,  2.38s/it]
ChatCompletion(id='chatcmpl-9MzCC5Z3LZb0PCQiC2cCcPfG2bcSQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international transfer", "transfer duration", "speed of transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265480, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=241, total_tokens=254))
["international transfer", "transfer duration", "speed of transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long to I have to wait for a transfer to reach my account?"

Keyphrases:
2073it [1:10:53,  2.10s/it]
ChatCompletion(id='chatcmpl-9MzCEexLzl2CNqq5QxiIL6V7BlcUv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer time", "fund transfer delay", "receiving transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265482, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["transfer time", "fund transfer delay", "receiving transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long is it going to take for my funds to show in my account?"

Keyphrases:
2074it [1:10:55,  2.04s/it]
ChatCompletion(id='chatcmpl-9MzCGUlSBW8kIpPdW7887fMAXVGk9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer time", "transaction processing time", "funds availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715265484, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["fund transfer time", "transaction processing time", "funds availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does a transfer take from the point it's sent, to the point it arrives in my account?"

Keyphrases:
2075it [1:10:57,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzCIAGL8KDgFNhdykTnf6egnMGfg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer duration", "transfer time", "money receiving time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265486, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=240, total_tokens=253))
["transfer duration", "transfer time", "money receiving time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long will it take for the transfer to reach my account?"

Keyphrases:
2076it [1:10:59,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzCJlVfvGyYxquEtta20qATnPeLq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer time", "expected transfer duration", "receiving funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715265487, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["transfer time", "expected transfer duration", "receiving funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If my transfer is from Europe how long will it take?"

Keyphrases:
2077it [1:11:00,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzCLoQq4qViQqlGm8Mwz17zXhG1T', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer duration", "international transfer time", "Europe transfer ETA"]', role='assistant', function_call=None, tool_calls=None))], created=1715265489, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["transfer duration", "international transfer time", "Europe transfer ETA"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is an important thing from China that I need to transfer. Approximately how long will this take?"

Keyphrases:
2078it [1:11:02,  1.89s/it]
ChatCompletion(id='chatcmpl-9MzCNgZOlPghSF1M0WZDGeudRsCaK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international transfer time", "transfer duration", "money transfer time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265491, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=238, total_tokens=252))
["international transfer time", "transfer duration", "money transfer time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does a transfer take from china?"

Keyphrases:
2079it [1:11:07,  2.60s/it]
ChatCompletion(id='chatcmpl-9MzCPXLUwpEg25VTu4wprS4kSHtUC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer duration", "international transfer time", "money transfer time"]', role='assistant', function_call=None, tool_calls=None))], created=1715265493, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["transfer duration", "international transfer time", "money transfer time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will money be available in my account?"

Keyphrases:
2080it [1:11:08,  2.28s/it]
ChatCompletion(id='chatcmpl-9MzCT1IhKjLvtl8MmF0ucpk5TYGI5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund availability", "account balance update", "money deposit timing"]', role='assistant', function_call=None, tool_calls=None))], created=1715265497, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["fund availability", "account balance update", "money deposit timing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think my card payment has been stopped"

Keyphrases:
2081it [1:11:10,  2.12s/it]
ChatCompletion(id='chatcmpl-9MzCVsi3yKi9UhxAcVp5Vb6BMlxs1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment issue", "stopped payment", "payment blocked"]', role='assistant', function_call=None, tool_calls=None))], created=1715265499, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["card payment issue", "stopped payment", "payment blocked"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card payment was reverted.  Why?"

Keyphrases:
2082it [1:11:11,  1.85s/it]
ChatCompletion(id='chatcmpl-9MzCWJpVJ3aU21BMVbT6Qvh4cXnGP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment reversal", "reverted payment", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265500, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["payment reversal", "reverted payment", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "the app reverted my payment"

Keyphrases:
2083it [1:11:12,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzCXmob6w3UKSfqFtzmOGXFiQVIg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment reversal", "reverted transaction", "app payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265501, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["payment reversal", "reverted transaction", "app payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card payment was cancelled."

Keyphrases:
2084it [1:11:15,  2.05s/it]
ChatCompletion(id='chatcmpl-9MzCZKqXnUGPx1I9w1NisqtAQxpSs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment cancellation", "payment status", "cancelled transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265503, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["card payment cancellation", "payment status", "cancelled transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was my payment cancelled?"

Keyphrases:
2085it [1:11:16,  1.80s/it]
ChatCompletion(id='chatcmpl-9MzCbUgS0B5VdaxZiferSxLgaq3Lf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment cancellation", "cancelled transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265505, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=8, prompt_tokens=224, total_tokens=232))
["payment cancellation", "cancelled transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a payment but the app reverted the payment."

Keyphrases:
2086it [1:11:18,  1.75s/it]
ChatCompletion(id='chatcmpl-9MzCde3JXbv2e9wauqxdENVJ7eARL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment reversal", "failed payment", "app error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265507, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["payment reversal", "failed payment", "app error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My payment was reverted by the app"

Keyphrases:
2087it [1:11:20,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzCevH0hGctcexnpKoYq6JXYrLnh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment reversal", "reverted transaction", "app transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265508, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["payment reversal", "reverted transaction", "app transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hello, My money went through for my purchase but now I got contacted from the seller noting that they didn't receive it. Then the money was returned to my account and I'm not sure why this occurred. So if you can resolve this issue please."

Keyphrases:
2088it [1:11:21,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzCgPGh6VUw2Sv7Wq6D68EOnAzZ3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment issue", "money reversal", "seller transaction problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265510, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=269, total_tokens=282))
["payment issue", "money reversal", "seller transaction problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please explain to me the circumstances in which my card payment would be reverted?"

Keyphrases:
2089it [1:11:23,  1.67s/it]
ChatCompletion(id='chatcmpl-9MzChxOJhQni8QGDQv3wT8aKdAxZY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reverted payment", "card payment issues", "payment reversal conditions"]', role='assistant', function_call=None, tool_calls=None))], created=1715265511, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["reverted payment", "card payment issues", "payment reversal conditions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why has my card payment been cancelled?"

Keyphrases:
2090it [1:11:26,  1.97s/it]
ChatCompletion(id='chatcmpl-9MzCjHr8G3uBuKobDml66v5SIMTMq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment issue", "payment cancellation", "cancelled transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265513, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card payment issue", "payment cancellation", "cancelled transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do if it says my card payment has been cancelled?"

Keyphrases:
2091it [1:11:27,  1.78s/it]
ChatCompletion(id='chatcmpl-9MzCmQmAyMUaRsjJdBSDLARZ16oY3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment issue", "cancelled card payment", "resolve payment cancellation"]', role='assistant', function_call=None, tool_calls=None))], created=1715265516, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["payment issue", "cancelled card payment", "resolve payment cancellation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm not sure why my account has been refunded a payment for an item I've already received about 2 weeks ago. Can you please tell me what is going on?"

Keyphrases:
2092it [1:11:29,  1.82s/it]
ChatCompletion(id='chatcmpl-9MzCnVGxjfvl9ZwKyRg3hpUp0siWR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund status", "unexpected refund", "payment query"]', role='assistant', function_call=None, tool_calls=None))], created=1715265517, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=253, total_tokens=265))
["refund status", "unexpected refund", "payment query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is being declined for a purchase. I bought items before and the card worked. Do you know what the problem is?"

Keyphrases:
2093it [1:11:31,  1.78s/it]
ChatCompletion(id='chatcmpl-9MzCpOmlYQne2kQPAJ1RrPGXM9vlS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "payment issue", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715265519, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=244, total_tokens=256))
["card declined", "payment issue", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell my why my card payment has been reverted."

Keyphrases:
2094it [1:11:32,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzCrDD8PNckreiU8LOEuqqwBaooO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment reversal", "reverted card payment", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265521, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["payment reversal", "reverted card payment", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "why did the app refuse to make an approved payment"

Keyphrases:
2095it [1:11:34,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzCsuqoMubQ8nOAyEUfIoWmcHB9l', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment refusal", "app error", "failed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265522, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["payment refusal", "app error", "failed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you know why my card payment was reverted?"

Keyphrases:
2096it [1:11:35,  1.59s/it]
ChatCompletion(id='chatcmpl-9MzCuHhmKolpH90aDXeqLypYkkgoH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment reversal", "card payment issue", "reverted transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265524, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["payment reversal", "card payment issue", "reverted transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My credit card cancelled a payment for a purchase."

Keyphrases:
2097it [1:11:50,  5.73s/it]
ChatCompletion(id='chatcmpl-9MzCv3jCmMOmOqrnJKeGDyVoqxXbd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment cancellation", "credit card issue", "unauthorized transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265525, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["payment cancellation", "credit card issue", "unauthorized transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was my payment reversed?"

Keyphrases:
2098it [1:11:53,  4.64s/it]
ChatCompletion(id='chatcmpl-9MzDBHmHh3q0TGBdKSgJuTKM1aJHH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment reversal", "reversed payment", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265541, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["payment reversal", "reversed payment", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a payment listed as cancelled."

Keyphrases:
2099it [1:11:54,  3.71s/it]
ChatCompletion(id='chatcmpl-9MzDDJ5PO2nQfbfhmvOcQ9AGKcGBa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment status", "cancelled payment", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265543, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["payment status", "cancelled payment", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think my card payment had been return"

Keyphrases:
2100it [1:11:55,  2.96s/it]
ChatCompletion(id='chatcmpl-9MzDE3eAGOUbgSHb2AS7ogMFQ8d6z', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment returned", "payment reversal", "failed card payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715265544, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["card payment returned", "payment reversal", "failed card payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was contacted by a seller with a message that they never received my money. I am 100% sure it was taken from my account so I definitely need this sorted out soon."

Keyphrases:
2101it [1:11:56,  2.42s/it]
ChatCompletion(id='chatcmpl-9MzDGYWfk6pWnze8pHeP2sTrchsqZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing payment", "payment dispute", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265546, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=255, total_tokens=267))
["missing payment", "payment dispute", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what happens to the funds if a merchant refuses the payment"

Keyphrases:
2102it [1:11:58,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzDHayBeD16VzDud4UYcfJqhdZjB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["merchant payment refusal", "refused payment resolution", "funds handling after refusal"]', role='assistant', function_call=None, tool_calls=None))], created=1715265547, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=230, total_tokens=248))
["merchant payment refusal", "refused payment resolution", "funds handling after refusal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am attempting to make a purchase online, but my card is not working.  I know there are funds available, is this an issue on the banks end?"

Keyphrases:
2103it [1:12:00,  2.09s/it]
ChatCompletion(id='chatcmpl-9MzDIeBy7cWoPwTD58H6sEwc5PpiO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card not working", "online purchase issue", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715265548, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=251, total_tokens=265))
["card not working", "online purchase issue", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was my card payment cancelled?"

Keyphrases:
2104it [1:12:01,  1.89s/it]
ChatCompletion(id='chatcmpl-9MzDKC8QprOJdPjgejSjQjUrm3CJn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment issue", "cancelled payment", "payment rejection"]', role='assistant', function_call=None, tool_calls=None))], created=1715265550, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["card payment issue", "cancelled payment", "payment rejection"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why has my card payment been reverted?"

Keyphrases:
2105it [1:12:03,  1.85s/it]
ChatCompletion(id='chatcmpl-9MzDMfpl6PrUOzR2Pib8NvO3ExIU4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment reversal", "reverted payment", "card payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265552, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["payment reversal", "reverted payment", "card payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There must be an issue, why has my card been cancelled?"

Keyphrases:
2106it [1:12:05,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzDNZasWNRKufRZN9I3cuCQ4zTBF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card cancellation", "issue with card", "why card cancelled"]', role='assistant', function_call=None, tool_calls=None))], created=1715265553, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["card cancellation", "issue with card", "why card cancelled"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I bought something and the money appeared back into my account? Why?"

Keyphrases:
2107it [1:12:06,  1.65s/it]
ChatCompletion(id='chatcmpl-9MzDPQVBiQOUsmGhFwAHOjmzQVRgD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["refund processing", "transaction reversal", "money returned"]', role='assistant', function_call=None, tool_calls=None))], created=1715265555, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["refund processing", "transaction reversal", "money returned"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My account shows the card payment cancelled."

Keyphrases:
2108it [1:12:07,  1.54s/it]
ChatCompletion(id='chatcmpl-9MzDQ4nBrEoeAjqoFLTmUPz2XCqgg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment status", "cancelled payment", "card payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265556, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["card payment status", "cancelled payment", "card payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm not sure why my card payment was cancelled, can you find out why?"

Keyphrases:
2109it [1:12:09,  1.54s/it]
ChatCompletion(id='chatcmpl-9MzDS1BinnZud88jSJ1xWfQLELAnU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment issue", "cancelled card payment", "investigate payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715265558, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["payment issue", "cancelled card payment", "investigate payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the reason that my card payment was cancelled?"

Keyphrases:
2110it [1:12:10,  1.54s/it]
ChatCompletion(id='chatcmpl-9MzDTq26xP9P4uIruqXOLAj6nJ94o', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card payment issue", "cancelled payment", "payment failure reason"]', role='assistant', function_call=None, tool_calls=None))], created=1715265559, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["card payment issue", "cancelled payment", "payment failure reason"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hi, I would like to file a claim for an inquiry. I am a frequent customer of the company in question and have never had any issue with my purchases, payments, or otherwise. However, the price deducted for an item I purchased a couple of weeks ago has been returned to my checking account. Was there an issue with my payment? The item has already been delivered to me."

Keyphrases:
2111it [1:12:12,  1.63s/it]
ChatCompletion(id='chatcmpl-9MzDVhcXNWsShxUqyzM6d9C0kieWm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment issue", "refund inquiry", "item price returned", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265561, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=296, total_tokens=313))
["payment issue", "refund inquiry", "item price returned", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was my card payment reverted?"

Keyphrases:
2112it [1:12:13,  1.51s/it]
ChatCompletion(id='chatcmpl-9MzDWiXBmrFvrFcOs7TUJc4pAoh6y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment reversal", "reverted card payment", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265562, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["payment reversal", "reverted card payment", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why does the app revert a payment?"

Keyphrases:
2113it [1:12:15,  1.45s/it]
ChatCompletion(id='chatcmpl-9MzDYaWR7V2fQRbCIt1xo7tRQdDg6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment reversal", "app error", "failed payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715265564, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["payment reversal", "app error", "failed payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I did a payment but the app reverted it"

Keyphrases:
2114it [1:12:16,  1.45s/it]
ChatCompletion(id='chatcmpl-9MzDZ7AHH63Ny1UDQGiGMLEVPKoZl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment reversal", "failed payment", "payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265565, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["payment reversal", "failed payment", "payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What happens if a merchant doesn't accept a payment?"

Keyphrases:
2115it [1:12:18,  1.48s/it]
ChatCompletion(id='chatcmpl-9MzDbCnlZZtAZtR6XfpaGywhgN2ox', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment rejection", "merchant payment issues", "failed payment resolution"]', role='assistant', function_call=None, tool_calls=None))], created=1715265567, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["payment rejection", "merchant payment issues", "failed payment resolution"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There was a canceled payment for my card."

Keyphrases:
2116it [1:12:20,  1.60s/it]
ChatCompletion(id='chatcmpl-9MzDcbjyOSzSR4mBM7VidTCxk8GVz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["canceled payment", "payment issue", "card payment reversal"]', role='assistant', function_call=None, tool_calls=None))], created=1715265568, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["canceled payment", "payment issue", "card payment reversal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transaction to pay for an item was returned to my account."

Keyphrases:
2117it [1:12:21,  1.57s/it]
ChatCompletion(id='chatcmpl-9MzDe3dR9Sah4Y8OVZimDQYtlCai1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction reversal", "payment return", "returned funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715265570, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["transaction reversal", "payment return", "returned funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone stopped my payment"

Keyphrases:
2118it [1:12:23,  1.53s/it]
ChatCompletion(id='chatcmpl-9MzDfXrlkes7XyO204eYgox1CnK25', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment stopped", "blocked payment", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265571, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["payment stopped", "blocked payment", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If my card payment is cancelled, what should I do?"

Keyphrases:
2119it [1:12:24,  1.56s/it]
ChatCompletion(id='chatcmpl-9MzDheuqikNK4CIJ9b85uTh1nMSBU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancelled card payment", "next steps after cancellation", "handling cancelled payments"]', role='assistant', function_call=None, tool_calls=None))], created=1715265573, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["cancelled card payment", "next steps after cancellation", "handling cancelled payments"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why has payment been returned?"

Keyphrases:
2120it [1:12:26,  1.52s/it]
ChatCompletion(id='chatcmpl-9MzDiTAk8NNESeWdJLCMaila48rej', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment returned", "failed payment", "refund issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715265574, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["payment returned", "failed payment", "refund issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What kind of cash machines would allow me to change my PIN?"

Keyphrases:
2121it [1:12:27,  1.44s/it]
ChatCompletion(id='chatcmpl-9MzDk8L9QcdmFE7tIzcuOnYT6jmaZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM services", "change PIN", "PIN update ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265576, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["ATM services", "change PIN", "PIN update ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I change my PIN?"

Keyphrases:
2122it [1:12:28,  1.40s/it]
ChatCompletion(id='chatcmpl-9MzDlgZZlGAxVeeCbNyEIslrC1nyX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["change PIN", "PIN modification", "PIN settings"]', role='assistant', function_call=None, tool_calls=None))], created=1715265577, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["change PIN", "PIN modification", "PIN settings"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is the bank the only place I can change my PIN>"

Keyphrases:
2123it [1:12:30,  1.41s/it]
ChatCompletion(id='chatcmpl-9MzDmMTiQOYsyblBKJzNFSR6lHh6N', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["change PIN", "PIN modification locations", "bank services for PIN change"]', role='assistant', function_call=None, tool_calls=None))], created=1715265578, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["change PIN", "PIN modification locations", "bank services for PIN change"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I am overseas, how do I change my pin?"

Keyphrases:
2124it [1:12:32,  1.70s/it]
ChatCompletion(id='chatcmpl-9MzDoNFxQzD8Xn3VS8alGw3h6y64z', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["overseas pin change", "change pin abroad", "modify pin internationally"]', role='assistant', function_call=None, tool_calls=None))], created=1715265580, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["overseas pin change", "change pin abroad", "modify pin internationally"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can i change my PIN at the ATM?"

Keyphrases:
2125it [1:12:33,  1.62s/it]
ChatCompletion(id='chatcmpl-9MzDqT9utRexkqtOYUIPHlycpZfYt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["change PIN", "ATM PIN update", "modify PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715265582, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["change PIN", "ATM PIN update", "modify PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How might  I change my PIN?"

Keyphrases:
2126it [1:12:35,  1.59s/it]
ChatCompletion(id='chatcmpl-9MzDs70VHGpSpe2YT4myNSq30lYjf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change", "update PIN", "modify PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715265584, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["PIN change", "update PIN", "modify PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to change my PIN but I am not currently in the country."

Keyphrases:
2127it [1:12:36,  1.51s/it]
ChatCompletion(id='chatcmpl-9MzDtU2fxGC1vj5GMNHXjwLV9B0dU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change", "overseas banking", "modify PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715265585, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["PIN change", "overseas banking", "modify PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to change my card PIN."

Keyphrases:
2128it [1:12:38,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzDvVmuRKkm5QNgiJWoLiFfwPPHk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["change PIN", "modify PIN", "PIN update"]', role='assistant', function_call=None, tool_calls=None))], created=1715265587, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["change PIN", "modify PIN", "PIN update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to set a new PIN"

Keyphrases:
2129it [1:12:40,  1.67s/it]
ChatCompletion(id='chatcmpl-9MzDwe3yYWrHXgbHVo8v6DLK84SRd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["set PIN", "change PIN", "new PIN setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715265588, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["set PIN", "change PIN", "new PIN setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I desperately need to change my PIN, but I'm overseas on vacation right now. How can I do this?"

Keyphrases:
2130it [1:12:41,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzDy1IX13YPAd34C30r9vIvZEv3K', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change", "overseas banking", "emergency service"]', role='assistant', function_call=None, tool_calls=None))], created=1715265590, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=241, total_tokens=255))
["PIN change", "overseas banking", "emergency service"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need a new Pin how do I go about that?"

Keyphrases:
2131it [1:12:43,  1.53s/it]
ChatCompletion(id='chatcmpl-9MzE00Ax1AnO9CMGISl6rFlIHg2lw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN reset", "new PIN request", "PIN change process"]', role='assistant', function_call=None, tool_calls=None))], created=1715265592, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["PIN reset", "new PIN request", "PIN change process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a location near me that i can change my PIN?"

Keyphrases:
2132it [1:12:44,  1.56s/it]
ChatCompletion(id='chatcmpl-9MzE1wn8r4F5NRgG66Z1pmGYIJoPl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change location", "nearest service center", "PIN modification site"]', role='assistant', function_call=None, tool_calls=None))], created=1715265593, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["PIN change location", "nearest service center", "PIN modification site"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "In what ATM can I change my pin?"

Keyphrases:
2133it [1:12:46,  1.50s/it]
ChatCompletion(id='chatcmpl-9MzE38Ezp30XGEkWr7sxn68HgSdr7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM services", "change pin", "pin update"]', role='assistant', function_call=None, tool_calls=None))], created=1715265595, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["ATM services", "change pin", "pin update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'd like to make a new PIN selection."

Keyphrases:
2134it [1:12:47,  1.47s/it]
ChatCompletion(id='chatcmpl-9MzE4pL7XIMQZ5IlquUlnmm5GgOd0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["set new PIN", "change PIN", "PIN update"]', role='assistant', function_call=None, tool_calls=None))], created=1715265596, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["set new PIN", "change PIN", "PIN update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I set a new pin?"

Keyphrases:
2135it [1:12:49,  1.55s/it]
ChatCompletion(id='chatcmpl-9MzE5FnPWLZkc04cKEDjXBtyHPwns', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["set pin", "change pin", "pin update"]', role='assistant', function_call=None, tool_calls=None))], created=1715265597, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["set pin", "change pin", "pin update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I update my PIN to a new number?"

Keyphrases:
2136it [1:12:50,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzE7PKDX1wrCelKUc6NmxavqtfFu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN update", "change PIN", "new PIN number"]', role='assistant', function_call=None, tool_calls=None))], created=1715265599, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["PIN update", "change PIN", "new PIN number"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I change my Tholepin ?"

Keyphrases:
2137it [1:12:52,  1.48s/it]
ChatCompletion(id='chatcmpl-9MzE8zr7UF1lFB04gKvZNC0FyUJ2A', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["change Tholepin", "reset Tholepin", "modify Tholepin security"]', role='assistant', function_call=None, tool_calls=None))], created=1715265600, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=19, prompt_tokens=228, total_tokens=247))
["change Tholepin", "reset Tholepin", "modify Tholepin security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My new pin needs to be set."

Keyphrases:
2138it [1:12:53,  1.43s/it]
ChatCompletion(id='chatcmpl-9MzEANQKg2UE7lugZrbFbCFNcQiYk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["set pin", "pin update", "new pin configuration"]', role='assistant', function_call=None, tool_calls=None))], created=1715265602, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["set pin", "pin update", "new pin configuration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to choose a different PIN."

Keyphrases:
2139it [1:12:56,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzEBntlyy1HjAJHefcidr4qctNro', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["change PIN", "PIN setup", "modify PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715265603, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["change PIN", "PIN setup", "modify PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to change my pin."

Keyphrases:
2140it [1:12:58,  2.02s/it]
ChatCompletion(id='chatcmpl-9MzEFfhUw5yQBwRbKF2s9KSrPIhyy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin change", "update pin", "reset pin"]', role='assistant', function_call=None, tool_calls=None))], created=1715265607, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["pin change", "update pin", "reset pin"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Am I able to change my PIN at any cash machines?"

Keyphrases:
2141it [1:13:00,  2.00s/it]
ChatCompletion(id='chatcmpl-9MzEG4boHH2SBJ7clNTdyUEyui37F', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change", "change PIN at ATM", "PIN modification"]', role='assistant', function_call=None, tool_calls=None))], created=1715265608, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["PIN change", "change PIN at ATM", "PIN modification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am travelling for two more weeks but really need to change my PIN asap. What do I do?"

Keyphrases:
2142it [1:13:02,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzEIm7YNaOgSIko92MoxrZEQTfPJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change urgent", "travel PIN change", "immediate PIN modification"]', role='assistant', function_call=None, tool_calls=None))], created=1715265610, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=240, total_tokens=256))
["PIN change urgent", "travel PIN change", "immediate PIN modification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to change my PIN. Can I do that at a cash machine?"

Keyphrases:
2143it [1:13:03,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzEK4cFPp6Ds3qYBW6EnJ5on55TB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change", "update PIN", "cash machine services"]', role='assistant', function_call=None, tool_calls=None))], created=1715265612, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["PIN change", "update PIN", "cash machine services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do cash machines let me change my pin?"

Keyphrases:
2144it [1:13:06,  2.00s/it]
ChatCompletion(id='chatcmpl-9MzELniWUiSG6Yy3iS4HWDVpynvad', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM services", "change pin", "PIN modification"]', role='assistant', function_call=None, tool_calls=None))], created=1715265613, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["ATM services", "change pin", "PIN modification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I change my PIN?"

Keyphrases:
2145it [1:13:07,  1.80s/it]
ChatCompletion(id='chatcmpl-9MzEOb3dBaW6IJWNMRl2r0s7BJVin', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change", "update PIN", "change PIN code"]', role='assistant', function_call=None, tool_calls=None))], created=1715265616, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["PIN change", "update PIN", "change PIN code"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to change my PIN."

Keyphrases:
2146it [1:13:09,  1.75s/it]
ChatCompletion(id='chatcmpl-9MzEPtRvM2yNR9ooJzAp197PedAJ5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change", "change security code", "reset PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715265617, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["PIN change", "change security code", "reset PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "May I receive a different card pin"

Keyphrases:
2147it [1:13:10,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzERTOBOviRUnhVomyyGHC6WQVBE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pin change request", "new pin", "change card pin"]', role='assistant', function_call=None, tool_calls=None))], created=1715265619, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["pin change request", "new pin", "change card pin"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I need to do to change my PIN?"

Keyphrases:
2148it [1:13:13,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzET25zm9vwXCbDiw3nmmCp5z3Hn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change", "update PIN", "change PIN procedure"]', role='assistant', function_call=None, tool_calls=None))], created=1715265621, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["PIN change", "update PIN", "change PIN procedure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help me set up a new PIN?"

Keyphrases:
2149it [1:13:14,  1.84s/it]
ChatCompletion(id='chatcmpl-9MzEVAscaaRUBb0v1jhFtWwRoT08r', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["set up PIN", "PIN configuration", "new PIN setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715265623, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["set up PIN", "PIN configuration", "new PIN setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Which cash machines will allow me to change my PIN?"

Keyphrases:
2150it [1:13:16,  1.87s/it]
ChatCompletion(id='chatcmpl-9MzEXRGHa1rX1wDLJmbQREQROK1qF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change", "ATM services", "change PIN at ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715265625, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["PIN change", "ATM services", "change PIN at ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am in Austria right now. I need to change my PIN ASAP, so can I still do this from here?"

Keyphrases:
2151it [1:13:18,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzEZhnKdktNfyq6b8o69P4CbEKrO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change", "overseas banking operation", "change PIN abroad"]', role='assistant', function_call=None, tool_calls=None))], created=1715265627, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=242, total_tokens=258))
["PIN change", "overseas banking operation", "change PIN abroad"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I find instructions to change my PIN?"

Keyphrases:
2152it [1:13:19,  1.59s/it]
ChatCompletion(id='chatcmpl-9MzEabXJbhfMAwF9DUa4xprNr9MP9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change instructions", "how to change PIN", "update PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715265628, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["PIN change instructions", "how to change PIN", "update PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to change my pin but I am on the road."

Keyphrases:
2153it [1:13:20,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzEb4R2DiJN5eiNhwFscRDE5LWTb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["change pin", "pin modification", "on-the-go service"]', role='assistant', function_call=None, tool_calls=None))], created=1715265629, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["change pin", "pin modification", "on-the-go service"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I update the PIN on my account?"

Keyphrases:
2154it [1:13:23,  1.94s/it]
ChatCompletion(id='chatcmpl-9MzEcsF1Y8vaCxJdU5kyboLEPcvrb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["update PIN", "change PIN", "PIN modification"]', role='assistant', function_call=None, tool_calls=None))], created=1715265630, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["update PIN", "change PIN", "PIN modification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need a new PIN."

Keyphrases:
2155it [1:13:26,  2.27s/it]
ChatCompletion(id='chatcmpl-9MzEgfzHQPE6jF44W061ej91AgL6C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN reset", "new PIN request", "change PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715265634, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["PIN reset", "new PIN request", "change PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Show me how to change my pin?"

Keyphrases:
2156it [1:13:28,  2.05s/it]
ChatCompletion(id='chatcmpl-9MzEjfkjWCkPWL4bCrGkJSdusBvl0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["change pin", "PIN update", "modify PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715265637, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["change pin", "PIN update", "modify PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please tell me which cash machines will allow me to change my pin."

Keyphrases:
2157it [1:13:30,  1.99s/it]
ChatCompletion(id='chatcmpl-9MzEk87Tllx2fdhPwQcpWVm70RiIx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM pin change", "change pin", "ATM services"]', role='assistant', function_call=None, tool_calls=None))], created=1715265638, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["ATM pin change", "change pin", "ATM services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What steps do I need to take to change my card PIN?"

Keyphrases:
2158it [1:13:32,  2.17s/it]
ChatCompletion(id='chatcmpl-9MzEnzc8OsvMNYG5xmlSXtG1B6bh7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change", "change card PIN", "modify PIN"]', role='assistant', function_call=None, tool_calls=None))], created=1715265641, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["PIN change", "change card PIN", "modify PIN"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How to change the PIN on my card?"

Keyphrases:
2159it [1:13:33,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzEp4QwQWxMDc2DHIkvxC2B7SnzC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change", "update PIN", "card security"]', role='assistant', function_call=None, tool_calls=None))], created=1715265643, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["PIN change", "update PIN", "card security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I change the PIN?  Do I have to go to a real bank?"

Keyphrases:
2160it [1:13:35,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzEqQ3txmOkY8bZe7NdY16qv8GKg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["PIN change", "change PIN procedure", "bank visit for PIN change"]', role='assistant', function_call=None, tool_calls=None))], created=1715265644, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=236, total_tokens=252))
["PIN change", "change PIN procedure", "bank visit for PIN change"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've tried numerous times to submit a transfer of funds. Why isn't it going through?"

Keyphrases:
2161it [1:13:36,  1.62s/it]
ChatCompletion(id='chatcmpl-9MzErFICw9t6SazsJgjNktW0bmtwB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["funds transfer issue", "transfer submission failure", "transfer not processing"]', role='assistant', function_call=None, tool_calls=None))], created=1715265645, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=237, total_tokens=253))
["funds transfer issue", "transfer submission failure", "transfer not processing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've transferred money before without issue but now I am encountering an error stating that it isn't possible. Why is that?"

Keyphrases:
2162it [1:13:38,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzEtagMqcqKX3T9hiL1yrdSiDDXo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer error", "money transfer issue", "transfer not possible"]', role='assistant', function_call=None, tool_calls=None))], created=1715265647, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=243, total_tokens=257))
["transfer error", "money transfer issue", "transfer not possible"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am not able to do a transfer to an account"

Keyphrases:
2163it [1:13:40,  1.70s/it]
ChatCompletion(id='chatcmpl-9MzEuqnDQYyow8JUb0s2GgD9OJpZL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issues", "unable to transfer", "transaction problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265648, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["transfer issues", "unable to transfer", "transaction problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was unable to make a transfer to another account."

Keyphrases:
2164it [1:13:41,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzEw3ewK0lOLIkDChfMwU87QWkAP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["failed transfer", "transfer issues", "unable to transfer funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715265650, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["failed transfer", "transfer issues", "unable to transfer funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I had a transfer blocked"

Keyphrases:
2165it [1:13:43,  1.58s/it]
ChatCompletion(id='chatcmpl-9MzEyuRP40Pk8Osr4ERHCO3hU8O0A', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["blocked transfer", "transfer issue", "unblock transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265652, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["blocked transfer", "transfer issue", "unblock transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you please help me with this exchange?  I am trying to get crypto and the app won't let me."

Keyphrases:
2166it [1:13:44,  1.47s/it]
ChatCompletion(id='chatcmpl-9MzEzcquzUuWIFBY6jVAgC02hoVVN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["crypto exchange", "app issue", "buying crypto"]', role='assistant', function_call=None, tool_calls=None))], created=1715265653, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=242, total_tokens=255))
["crypto exchange", "app issue", "buying crypto"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I do a successful transfer to an account?"

Keyphrases:
2167it [1:13:46,  1.49s/it]
ChatCompletion(id='chatcmpl-9MzF0BgIWki5u0Ub7vkY1YPn5exd2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer process", "successful transfer", "fund transfer instructions"]', role='assistant', function_call=None, tool_calls=None))], created=1715265654, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["transfer process", "successful transfer", "fund transfer instructions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I get a message saying that my transfer is not possible?  I have done this before no problem.  Please fix."

Keyphrases:
2168it [1:13:47,  1.44s/it]
ChatCompletion(id='chatcmpl-9MzF2h89C4Bv7EeFw7vNbmYnN3uWI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "transfer not possible", "failed transfer resolution"]', role='assistant', function_call=None, tool_calls=None))], created=1715265656, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=245, total_tokens=259))
["transfer issue", "transfer not possible", "failed transfer resolution"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hey I want to buy some crypto but the app doesn't allow me to! What's the issue, I really want to exchange this"

Keyphrases:
2169it [1:13:49,  1.53s/it]
ChatCompletion(id='chatcmpl-9MzF3Dq3jhc4sWpVwbixiGtiFUhaM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["crypto purchase issue", "app restriction", "exchange crypto"]', role='assistant', function_call=None, tool_calls=None))], created=1715265657, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=246, total_tokens=259))
["crypto purchase issue", "app restriction", "exchange crypto"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to transfer money but it said it wasn't possible? I've done this before and it worked why isn't it working now?"

Keyphrases:
2170it [1:13:50,  1.50s/it]
ChatCompletion(id='chatcmpl-9MzF5k3bpo2l2eBDBsiOnGX6PQCeu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer issue", "transfer not possible", "failed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265659, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=246, total_tokens=260))
["money transfer issue", "transfer not possible", "failed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I transfer to a beneficiary?"

Keyphrases:
2171it [1:13:51,  1.48s/it]
ChatCompletion(id='chatcmpl-9MzF6A4PhCImGtJimuqe9IOsGnNF5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "beneficiary transfer problem", "unable to transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265660, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["transfer issue", "beneficiary transfer problem", "unable to transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am having problems transferring to a beneficiary."

Keyphrases:
2172it [1:13:53,  1.53s/it]
ChatCompletion(id='chatcmpl-9MzF86AuFXkicupQ9tXujxoiKQjY5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issues", "beneficiary transfer problem", "failed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265662, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["transfer issues", "beneficiary transfer problem", "failed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What's the deal with no cryptocurrency on your app?"

Keyphrases:
2173it [1:13:55,  1.53s/it]
ChatCompletion(id='chatcmpl-9MzF9awfVqKvaBXu2rqqAmb1KG0Sr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cryptocurrency support", "crypto availability", "digital currency options"]', role='assistant', function_call=None, tool_calls=None))], created=1715265663, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["cryptocurrency support", "crypto availability", "digital currency options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why isn't my transfer not going through? I keep getting an error message."

Keyphrases:
2174it [1:13:56,  1.50s/it]
ChatCompletion(id='chatcmpl-9MzFBC5YTxWg3dqfRlVfiyFJQ7UtH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer error", "failed transaction", "transaction issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715265665, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=234, total_tokens=246))
["transfer error", "failed transaction", "transaction issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the rules for transferring to a beneficiary?"

Keyphrases:
2175it [1:13:58,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzFCXtavj5WyJphUhmIcIhBA3Adg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer rules", "beneficiary transfer guidelines", "bank transfer conditions"]', role='assistant', function_call=None, tool_calls=None))], created=1715265666, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["transfer rules", "beneficiary transfer guidelines", "bank transfer conditions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I transfer money to a beneficiery?"

Keyphrases:
2176it [1:14:00,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzFFnsyXB40Cedh0leHnnXQWO6Sd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "send money", "transfer to beneficiary"]', role='assistant', function_call=None, tool_calls=None))], created=1715265669, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["money transfer", "send money", "transfer to beneficiary"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have tried transferring money numerous times.  All I keep getting is an error message.  Can you tell me what is going on and how this van be fixed?"

Keyphrases:
2177it [1:14:02,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzFGL4Bw1Ev0zJ8GEE4zL1PITNcr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer error", "money transfer issue", "transaction troubleshooting"]', role='assistant', function_call=None, tool_calls=None))], created=1715265670, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=252, total_tokens=265))
["transfer error", "money transfer issue", "transaction troubleshooting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a cryptocurrency exchange that won't go through. Please help me process it."

Keyphrases:
2178it [1:14:04,  1.84s/it]
ChatCompletion(id='chatcmpl-9MzFIbOBIg13dutFjZ2iaDd0oVJc8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cryptocurrency exchange issue", "failed crypto transaction", "crypto transfer problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265672, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=235, total_tokens=251))
["cryptocurrency exchange issue", "failed crypto transaction", "crypto transfer problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why wasn't I able to transfer to another account?"

Keyphrases:
2179it [1:14:05,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzFK4F8lGmCjybWMTEE7fDxzWE7U', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "unable to transfer", "account transfer problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265674, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["transfer issue", "unable to transfer", "account transfer problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The money would not transfer to a beneficiary."

Keyphrases:
2180it [1:14:07,  1.62s/it]
ChatCompletion(id='chatcmpl-9MzFMu7lJueocGZoiRntEo23NxLPQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issues", "beneficiary transfer problem", "failed money transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265676, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["transfer issues", "beneficiary transfer problem", "failed money transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How come I'm not allowed to transfer funds right now? I just keep getting an error message."

Keyphrases:
2181it [1:14:09,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzFN5lrjzz6qrkMtaHeBMwKFpDTt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["funds transfer issue", "error message", "transfer restriction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265677, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=238, total_tokens=252))
["funds transfer issue", "error message", "transfer restriction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I couldn't do a transfer to an account"

Keyphrases:
2182it [1:14:10,  1.70s/it]
ChatCompletion(id='chatcmpl-9MzFP15nShRaD04p27wrbIj7J2RWT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer", "unable to transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265679, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["transfer issue", "failed transfer", "unable to transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "A transfer to an account was not allowed"

Keyphrases:
2183it [1:14:12,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzFR1PkLiSyHmNXFf4UuWrkdowrs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "blocked transfer", "transfer not allowed"]', role='assistant', function_call=None, tool_calls=None))], created=1715265681, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["transfer issue", "blocked transfer", "transfer not allowed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I receive an error message saying that my transfer was not possible?"

Keyphrases:
2184it [1:14:13,  1.58s/it]
ChatCompletion(id='chatcmpl-9MzFSuSRMVQK4rgdzuDRe3E3Fbhkx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer error", "failed transaction", "transfer not possible"]', role='assistant', function_call=None, tool_calls=None))], created=1715265682, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["transfer error", "failed transaction", "transfer not possible"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Explain why I can't do a transfer to a beneficiary."

Keyphrases:
2185it [1:14:15,  1.50s/it]
ChatCompletion(id='chatcmpl-9MzFU1XFe1ppbdUro4g0XwAbMpN5d', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "beneficiary transfer problem", "unable to transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265684, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["transfer issue", "beneficiary transfer problem", "unable to transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer to beneficiary didn't go through"

Keyphrases:
2186it [1:14:16,  1.58s/it]
ChatCompletion(id='chatcmpl-9MzFVYpPrqSlokD8KgDm7tOMmkGPv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer", "beneficiary transfer problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265685, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["transfer issue", "failed transfer", "beneficiary transfer problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why isn't my transfer going through? I get a message saying it's not possible. I've had no issues in the past."

Keyphrases:
2187it [1:14:18,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzFXNe0UMReoNEJIDa0lG5tCMzO3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer", "transfer not possible", "error message transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265687, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=245, total_tokens=263))
["transfer issue", "failed transfer", "transfer not possible", "error message transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I couldn't make a transfer to a beneficiary!"

Keyphrases:
2188it [1:14:20,  1.59s/it]
ChatCompletion(id='chatcmpl-9MzFYffPDVfxxPu3ZvYQSWFSYpF9Z', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["failed transfer", "transfer issue", "beneficiary transfer problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265688, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["failed transfer", "transfer issue", "beneficiary transfer problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My beneficiary has been denied, is this normal?"

Keyphrases:
2189it [1:14:23,  2.06s/it]
ChatCompletion(id='chatcmpl-9MzFb8DbqcUKgVYZSYBJDDDWTHKjb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["beneficiary denial", "denied transactions", "account restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715265691, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["beneficiary denial", "denied transactions", "account restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am trying to exchange crypto and it's not working. Tell me how to fix this."

Keyphrases:
2190it [1:14:25,  2.00s/it]
ChatCompletion(id='chatcmpl-9MzFdQV5D5QCA7AXDyoNc7pRLj9D5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["crypto exchange issue", "troubleshoot crypto", "crypto not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715265693, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=237, total_tokens=253))
["crypto exchange issue", "troubleshoot crypto", "crypto not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The account transfer I was trying to do failed."

Keyphrases:
2191it [1:14:27,  2.17s/it]
ChatCompletion(id='chatcmpl-9MzFfImbXn3eZoREbQDT1f5RlyXzN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["failed transfer", "transfer issue", "transaction problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265695, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["failed transfer", "transfer issue", "transaction problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My beneficiary is not allowed, please may I have answer as to why this is?"

Keyphrases:
2192it [1:14:29,  1.92s/it]
ChatCompletion(id='chatcmpl-9MzFhrOuaU0LRT8cmlxhn1Yz1Fxan', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["beneficiary issues", "beneficiary rejection", "account restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715265697, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["beneficiary issues", "beneficiary rejection", "account restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why couldn't I do a transfer to a beneficiary?"

Keyphrases:
2193it [1:14:30,  1.85s/it]
ChatCompletion(id='chatcmpl-9MzFjhQ4pO2NBpHbcYpdxyjRxuCLN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "beneficiary transfer problem", "unable to transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265699, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["transfer issue", "beneficiary transfer problem", "unable to transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why would i not be able to do a transfer to a beneficiary?"

Keyphrases:
2194it [1:14:32,  1.77s/it]
ChatCompletion(id='chatcmpl-9MzFkvY7EUh4S6jdSIoy7FrDBGynU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer restrictions", "beneficiary issues", "transfer inability"]', role='assistant', function_call=None, tool_calls=None))], created=1715265700, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["transfer restrictions", "beneficiary issues", "transfer inability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to transfer money to a beneficiery. Why can't I?"

Keyphrases:
2195it [1:14:36,  2.57s/it]
ChatCompletion(id='chatcmpl-9MzFmofGAGn1mGdWqkB2ijpAdMXoy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer issue", "transfer not working", "beneficiary transfer problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265702, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["money transfer issue", "transfer not working", "beneficiary transfer problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you help with a transfer to an account"

Keyphrases:
2196it [1:14:38,  2.25s/it]
ChatCompletion(id='chatcmpl-9MzFrfuGysvFnCVlf0a3V8XPzlagH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer assistance", "account transfer help", "transfer support"]', role='assistant', function_call=None, tool_calls=None))], created=1715265707, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["money transfer assistance", "account transfer help", "transfer support"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "why isnt my account allowing transfers"

Keyphrases:
2197it [1:14:42,  2.81s/it]
ChatCompletion(id='chatcmpl-9MzFsJniuVLcsKoUD6t2ZrLjCq8K7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issues", "account restrictions", "enable transfers"]', role='assistant', function_call=None, tool_calls=None))], created=1715265708, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["transfer issues", "account restrictions", "enable transfers"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to buy cryptocurrency, but your app doesn't let me. Why?"

Keyphrases:
2198it [1:14:43,  2.36s/it]
ChatCompletion(id='chatcmpl-9MzFwrHyVtk6OsZZQiP75UWOpbBTa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cryptocurrency purchase", "app functionality", "buying restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715265712, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["cryptocurrency purchase", "app functionality", "buying restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "i tried to make a transfer to a beneficiary and it didn't go through"

Keyphrases:
2199it [1:14:45,  2.05s/it]
ChatCompletion(id='chatcmpl-9MzFxAKFNsVTVbhJxpCUfR5t3muiU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["failed transfer", "transfer error", "beneficiary transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265713, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["failed transfer", "transfer error", "beneficiary transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was a transfer to an account not allowed?"

Keyphrases:
2200it [1:14:46,  1.81s/it]
ChatCompletion(id='chatcmpl-9MzFzXYudzbjqKLLMnGye2T0B237E', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer restrictions", "blocked transfer", "transfer not allowed"]', role='assistant', function_call=None, tool_calls=None))], created=1715265715, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["transfer restrictions", "blocked transfer", "transfer not allowed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When I made a transfer, there was a fee.  Why?"

Keyphrases:
2201it [1:14:47,  1.79s/it]
ChatCompletion(id='chatcmpl-9MzG0tiKibTQxG5TPmF0srFIrKQah', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "fee explanation", "transaction cost"]', role='assistant', function_call=None, tool_calls=None))], created=1715265716, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["transfer fee", "fee explanation", "transaction cost"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was charged a fee for my transfer."

Keyphrases:
2202it [1:14:50,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzG2RSjY02F1Yk1HrFaprgUgGwsj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "fee complaint", "unexplained charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715265718, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["transfer fee", "fee complaint", "unexplained charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a reason I was charged a fee to transfer?"

Keyphrases:
2203it [1:14:51,  1.77s/it]
ChatCompletion(id='chatcmpl-9MzG4fKgaZnVN7KrckbxO6v2cmCAu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "reason for charge", "fee explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715265720, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["transfer fee", "reason for charge", "fee explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was a charged just for transferring?"

Keyphrases:
2204it [1:14:52,  1.61s/it]
ChatCompletion(id='chatcmpl-9MzG5HgDHnAqIfWHViFWo3cEAnCDR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fees", "transaction charges", "fee inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715265721, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["transfer fees", "transaction charges", "fee inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I had to pay in order to do a transfer"

Keyphrases:
2205it [1:14:54,  1.55s/it]
ChatCompletion(id='chatcmpl-9MzG73wgVRhZ5N52mR2myoLnmaApz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "payment for transfer", "cost of transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265723, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["transfer fee", "payment for transfer", "cost of transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the transfer fee charge?"

Keyphrases:
2206it [1:14:55,  1.55s/it]
ChatCompletion(id='chatcmpl-9MzG8NTM2ZSliiNYrDyumDtxLoo8F', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "fee details", "cost of transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265724, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["transfer fee", "fee details", "cost of transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I charged extra for transferring money?"

Keyphrases:
2207it [1:14:57,  1.56s/it]
ChatCompletion(id='chatcmpl-9MzG9I9ElnHpiBd6NSPzyHIws5cgs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra charge", "transfer fee", "unexpected fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715265725, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["extra charge", "transfer fee", "unexpected fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "im not paying this transfer fee"

Keyphrases:
2208it [1:14:59,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzGBzQfPiuCdu69z6fC61FT3M0aH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["waive fee", "transfer fee complaint", "refuse fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715265727, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["waive fee", "transfer fee complaint", "refuse fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am being charged a transfer fee aren't they free?"

Keyphrases:
2209it [1:15:00,  1.65s/it]
ChatCompletion(id='chatcmpl-9MzGDz1pCBsREEHG235EXRpcGNYKd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "fee complaint", "fee clarification"]', role='assistant', function_call=None, tool_calls=None))], created=1715265729, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["transfer fee", "fee complaint", "fee clarification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the maximum I can transfer before I incur fees?"

Keyphrases:
2210it [1:15:03,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzGFKoFdZBv4VFaW5fuMTCRZsA5k', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer limits", "fee thresholds", "maximum transfer amount"]', role='assistant', function_call=None, tool_calls=None))], created=1715265731, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["transfer limits", "fee thresholds", "maximum transfer amount"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got 2 transfer fees and I thought transfers were free."

Keyphrases:
2211it [1:15:05,  1.91s/it]
ChatCompletion(id='chatcmpl-9MzGHi6MJGyOlQhf3EwafFYvGDxr3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fees", "unexpected fees", "fee inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715265733, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["transfer fees", "unexpected fees", "fee inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why am I being charged a fee for transferring money?"

Keyphrases:
2212it [1:15:06,  1.85s/it]
ChatCompletion(id='chatcmpl-9MzGJqCKoDRPbt1z45cIU3agKSiIZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "money transfer charge", "unexplained fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715265735, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["transfer fee", "money transfer charge", "unexplained fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do charge fees for transfers?"

Keyphrases:
2213it [1:15:09,  1.97s/it]
ChatCompletion(id='chatcmpl-9MzGLLDjWV5nCwHDodhzUzwnmbm8c', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fees", "transaction cost", "banking fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715265737, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["transfer fees", "transaction cost", "banking fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I recently got a new place while I'm staying abroad and have been using this account to manage payments, but suddenly I am seeing fees increase. Where are these additional fees coming from?"

Keyphrases:
2214it [1:15:11,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzGNDSpVZxmdyeMXcJhoH0OUiwXq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign transaction fees", "increased charges", "unexplained fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715265739, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=255, total_tokens=270))
["foreign transaction fees", "increased charges", "unexplained fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hi,  Please help me, as i have transferred some amount but receiver did not get the same amount. He received a bit less. Due to this again i need to transfer the difference.   I have transferred money but beneficiary's account is credited with less amount. Now i have transfer the difference of the amount. I think there is some issue, could you please look into this."

Keyphrases:
2215it [1:15:13,  2.07s/it]
ChatCompletion(id='chatcmpl-9MzGP2Gqyd4jYXMTR4Nyo6SnhYPlP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer discrepancy", "incorrect amount received", "resend difference"]', role='assistant', function_call=None, tool_calls=None))], created=1715265741, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=296, total_tokens=310))
["transfer discrepancy", "incorrect amount received", "resend difference"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I get charged for something I bought online? Even though it was international, I thought it would be covered."

Keyphrases:
2216it [1:15:16,  2.27s/it]
ChatCompletion(id='chatcmpl-9MzGRipWgHcP8oGb2kLvtrUMzOjGV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international charges", "unexpected charges", "online purchase fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715265743, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=242, total_tokens=255))
["international charges", "unexpected charges", "online purchase fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why were there additional charges when transferring?"

Keyphrases:
2217it [1:15:17,  2.00s/it]
ChatCompletion(id='chatcmpl-9MzGUNdhT9JXaJBfH5WWMPuUUNOIc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional charges", "transfer fees", "unexpected fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715265746, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["additional charges", "transfer fees", "unexpected fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was charged more when I transferred!"

Keyphrases:
2218it [1:15:18,  1.80s/it]
ChatCompletion(id='chatcmpl-9MzGV2n0EmtXCFkgLZVEaawRyNn7S', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["overcharge", "transfer charge discrepancy", "incorrect charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715265747, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["overcharge", "transfer charge discrepancy", "incorrect charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a transfer fee?"

Keyphrases:
2219it [1:15:20,  1.77s/it]
ChatCompletion(id='chatcmpl-9MzGXW7ZdTA4SNFHdxHstAebbAp4c', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "cost of transfer", "transaction charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715265749, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["transfer fee", "cost of transfer", "transaction charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm not sure why I was charged an extra fee for transferring funds."

Keyphrases:
2220it [1:15:23,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzGZudNtSdah2tz5PjjhsAOM9IxG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra fee", "funds transfer fee", "unexpected charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715265751, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["extra fee", "funds transfer fee", "unexpected charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I thought transfers were free, why was I charged a fee?"

Keyphrases:
2221it [1:15:24,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzGb7jyZpjB77Nb48FuSRUAnSwqJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "unexpected charges", "service fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715265753, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["transfer fee", "unexpected charges", "service fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My receipt shows an extra charge on my transfer, why is this?"

Keyphrases:
2222it [1:15:26,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzGd9suxq6Mni1BChrYKmRge6KJ8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra charge", "transaction fee", "transfer discrepancies"]', role='assistant', function_call=None, tool_calls=None))], created=1715265755, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["extra charge", "transaction fee", "transfer discrepancies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was charged a fee when making this transfer, and I don't think I should have been!"

Keyphrases:
2223it [1:15:28,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzGemlLdAjRtxvrIPvdy2fvQ9R9U', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unjustified fee", "fee dispute", "transfer charge issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265756, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=238, total_tokens=253))
["unjustified fee", "fee dispute", "transfer charge issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I sent out money, but was charged extra for transferring. Why?"

Keyphrases:
2224it [1:15:29,  1.65s/it]
ChatCompletion(id='chatcmpl-9MzGgWWPvonHotHiwysXadkEjvpX1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra charges", "transfer fees", "unexpected fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715265758, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["extra charges", "transfer fees", "unexpected fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why am I seeing a transfer fee?"

Keyphrases:
2225it [1:15:30,  1.49s/it]
ChatCompletion(id='chatcmpl-9MzGhNZh4B91DBvbPakpcpzTjax0z', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "unexpected fee", "transaction charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715265759, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["transfer fee", "unexpected fee", "transaction charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There was an extra charge when I made a transfer."

Keyphrases:
2226it [1:15:31,  1.42s/it]
ChatCompletion(id='chatcmpl-9MzGiaXDKPRw9uy1mXQXfhQ8ITfHr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra charge", "billing issue", "transfer charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715265760, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["extra charge", "billing issue", "transfer charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need someone to alert me as to what's going on. I had transferred an amount but the receiver is saying that the amount is somewhat less than what I sent over. I now have to make another transfer to make up the difference."

Keyphrases:
2227it [1:15:33,  1.45s/it]
ChatCompletion(id='chatcmpl-9MzGk2QMpPgY13BHn1u8ADriXwtze', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "transfer discrepancy", "funds mismatch"]', role='assistant', function_call=None, tool_calls=None))], created=1715265762, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=266, total_tokens=279))
["transfer issue", "transfer discrepancy", "funds mismatch"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was charge a fee for my transfer, why?"

Keyphrases:
2228it [1:15:34,  1.37s/it]
ChatCompletion(id='chatcmpl-9MzGlblBA6aB5gLZNZF85ASspjBv9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "fee explanation", "why fee charged"]', role='assistant', function_call=None, tool_calls=None))], created=1715265763, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["transfer fee", "fee explanation", "why fee charged"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was there a fee for my transfer?"

Keyphrases:
2229it [1:15:39,  2.30s/it]
ChatCompletion(id='chatcmpl-9MzGpBIZdkBEuV1H6g55Fgjj5dKh1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "fee inquiry", "transfer charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715265767, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["transfer fee", "fee inquiry", "transfer charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was my transfer charged fees?"

Keyphrases:
2230it [1:15:40,  2.10s/it]
ChatCompletion(id='chatcmpl-9MzGrBWG4VES1TZL52QhdHC9YMbUR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fees", "fee details", "why fees charged"]', role='assistant', function_call=None, tool_calls=None))], created=1715265769, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["transfer fees", "fee details", "why fees charged"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there supposed to be a fee for the transfer I made?"

Keyphrases:
2231it [1:15:42,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzGtx217Ok8lWj5Sba1JPIuf6tT7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "banking fee", "transaction charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715265771, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["transfer fee", "banking fee", "transaction charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "In the past month I often used this account to manage payments for my new holiday villa. Now all of a sudden your fees have increased exorbitantly! Don't you have a rewards programme for frequent users?"

Keyphrases:
2232it [1:15:44,  2.12s/it]
ChatCompletion(id='chatcmpl-9MzGuNAGiqriHWUlrWsYkenhVTArK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fee increase complaint", "rewards program inquiry", "bank charge issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265772, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=260, total_tokens=276))
["fee increase complaint", "rewards program inquiry", "bank charge issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I charged a fee for a transfer?"

Keyphrases:
2233it [1:15:46,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzGxJmz7mzKh9Ly1iJLEn91HJ8W5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "fee explanation", "unexplained charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715265775, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["transfer fee", "fee explanation", "unexplained charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What extra charges are there?"

Keyphrases:
2234it [1:15:47,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzGyGpSiFwd13rhLbS9q47ghe0vm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional fees", "extra costs", "service charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715265776, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["additional fees", "extra costs", "service charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I know that I am able to make transfers for free.  That was something that I valued.  After I bought something online from abroad I noticed that I got charged a fee?  What is this and can it be removed?"

Keyphrases:
2235it [1:15:48,  1.58s/it]
ChatCompletion(id='chatcmpl-9MzGzlU77EV5lHkG3EPotlkBdXFhR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international transaction fee", "hidden charges", "fee removal request"]', role='assistant', function_call=None, tool_calls=None))], created=1715265777, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=265, total_tokens=279))
["international transaction fee", "hidden charges", "fee removal request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I transferred money and was charged and want to know why."

Keyphrases:
2236it [1:15:53,  2.40s/it]
ChatCompletion(id='chatcmpl-9MzH1pUWey2eXIb594S50oV5OlxUl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer charges", "transfer fee explanation", "why was I charged"]', role='assistant', function_call=None, tool_calls=None))], created=1715265779, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["money transfer charges", "transfer fee explanation", "why was I charged"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was charged for something I didn't expect"

Keyphrases:
2237it [1:15:55,  2.51s/it]
ChatCompletion(id='chatcmpl-9MzH5B4XZsBHseCHxDM8u2szMC1il', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unexpected charge", "dispute transaction", "billing error"]', role='assistant', function_call=None, tool_calls=None))], created=1715265783, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["unexpected charge", "dispute transaction", "billing error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I purchased some makeup through a site in China, and I was under the impression that when I make transfers there is no fee.  Why am I seeing this fee now?  I am not happy about this at all."

Keyphrases:
2238it [1:15:57,  2.17s/it]
ChatCompletion(id='chatcmpl-9MzH8HGetHauVEOeAs18EBCqPrQ57', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international transfer fee", "hidden fees", "transfer charges explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715265786, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=263, total_tokens=277))
["international transfer fee", "hidden fees", "transfer charges explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got charged and extra fee when I transferred money so why was I charged?"

Keyphrases:
2239it [1:15:58,  2.06s/it]
ChatCompletion(id='chatcmpl-9MzH9iA4OWLrYq1B2YLd6JNX56dNN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra fee", "money transfer charge", "fee explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715265787, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["extra fee", "money transfer charge", "fee explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you explain the transfer fee to me?"

Keyphrases:
2240it [1:16:01,  2.27s/it]
ChatCompletion(id='chatcmpl-9MzHBvLmm6h2IOxxI0asyD0FaECzc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer fee", "fee explanation", "transaction costs"]', role='assistant', function_call=None, tool_calls=None))], created=1715265789, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["transfer fee", "fee explanation", "transaction costs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will salary be received through this?"

Keyphrases:
2241it [1:16:03,  1.99s/it]
ChatCompletion(id='chatcmpl-9MzHDFeFrwhBILjOvah3ralPUj5WE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary deposit", "receiving salary", "salary transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265791, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["salary deposit", "receiving salary", "salary transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I get paid in a different currency?"

Keyphrases:
2242it [1:16:04,  1.97s/it]
ChatCompletion(id='chatcmpl-9MzHFFJqYKbQL3yPpIBKQF8MolXSt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "receive money in foreign currency", "multi-currency payments"]', role='assistant', function_call=None, tool_calls=None))], created=1715265793, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["currency exchange", "receive money in foreign currency", "multi-currency payments"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I receive my salary in a currency other than what it is deposited in?"

Keyphrases:
2243it [1:16:06,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzHHNpUoLp6BYO43FC7RDXrqjkXY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary currency conversion", "currency exchange", "foreign currency deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715265795, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["salary currency conversion", "currency exchange", "foreign currency deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get my salary through this?"

Keyphrases:
2244it [1:16:08,  1.79s/it]
ChatCompletion(id='chatcmpl-9MzHI7pYuf8QNEwsxYKCgWrCeoGTM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary deposit", "receiving salary", "direct deposit eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715265796, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["salary deposit", "receiving salary", "direct deposit eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can someone send me money?"

Keyphrases:
2245it [1:16:10,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzHKG8wdmUx58hUo0xqqGKm32MUJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["receive money", "incoming transfer", "money sending process"]', role='assistant', function_call=None, tool_calls=None))], created=1715265798, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["receive money", "incoming transfer", "money sending process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a problem with receiving my salary in GBP?"

Keyphrases:
2246it [1:16:11,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzHMUmjO7fGrmGXztzO5QSARPrmc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency issue", "receiving salary", "GBP transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715265800, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["currency issue", "receiving salary", "GBP transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I need to choose GBP to get my salary deposited properly?"

Keyphrases:
2247it [1:16:13,  1.71s/it]
ChatCompletion(id='chatcmpl-9MzHO6US5YQAsXeoPTFT2FDusu8MJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary deposit", "currency selection", "GBP deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715265802, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["salary deposit", "currency selection", "GBP deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I get paid in GBP. Should I configure this and if so, where?"

Keyphrases:
2248it [1:16:15,  1.84s/it]
ChatCompletion(id='chatcmpl-9MzHPb6IdFpNlN1iv6DFEtMBc6J0Q', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency settings", "GBP configuration", "payment currency setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715265803, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["currency settings", "GBP configuration", "payment currency setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible for me to get money out in a different currency?"

Keyphrases:
2249it [1:16:16,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzHRUVAaZjc8h3Cy2prE162rQNTm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign currency withdrawal", "multicurrency services", "international withdrawal"]', role='assistant', function_call=None, tool_calls=None))], created=1715265805, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["foreign currency withdrawal", "multicurrency services", "international withdrawal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use this to receive my salary?"

Keyphrases:
2250it [1:16:17,  1.54s/it]
ChatCompletion(id='chatcmpl-9MzHTQlZcCAPxJhkDXrzMLZdCnmu6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary deposit", "direct deposit eligibility", "receiving salary through bank"]', role='assistant', function_call=None, tool_calls=None))], created=1715265807, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["salary deposit", "direct deposit eligibility", "receiving salary through bank"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My salary is received in the form of GBP. Do I need to do anything specific to configure this?"

Keyphrases:
2251it [1:16:19,  1.55s/it]
ChatCompletion(id='chatcmpl-9MzHUxSicNBW2daKPGzb0VuvGGOPU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency configuration", "salary deposit", "GBP account settings"]', role='assistant', function_call=None, tool_calls=None))], created=1715265808, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=239, total_tokens=252))
["currency configuration", "salary deposit", "GBP account settings"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do people send me money?"

Keyphrases:
2252it [1:16:22,  1.94s/it]
ChatCompletion(id='chatcmpl-9MzHVfMIBsDcFiTb0JDXD4uIZwTnz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["receiving money", "money transfer to account", "how to receive transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265809, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=225, total_tokens=242))
["receiving money", "money transfer to account", "how to receive transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is GBP a supported currency?"

Keyphrases:
2253it [1:16:24,  1.92s/it]
ChatCompletion(id='chatcmpl-9MzHYoKYRfIqOdjusQxGO6R9BoVYZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency support", "GBP support", "supported currencies"]', role='assistant', function_call=None, tool_calls=None))], created=1715265812, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["currency support", "GBP support", "supported currencies"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I need to establish I am paid in GBP before a transfer?"

Keyphrases:
2254it [1:16:27,  2.38s/it]
ChatCompletion(id='chatcmpl-9MzHaV5AHHLDc7IVIAUUXTv5sxsLr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency setup", "GBP transfer requirement", "currency confirmation before transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265814, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["currency setup", "GBP transfer requirement", "currency confirmation before transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Salary in GBP has been received, does it need to be configured elsewhere?"

Keyphrases:
2255it [1:16:30,  2.53s/it]
ChatCompletion(id='chatcmpl-9MzHdiShpopUX7XwbdziqBV7mqHNs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary deposit", "currency configuration", "GBP account settings"]', role='assistant', function_call=None, tool_calls=None))], created=1715265817, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["salary deposit", "currency configuration", "GBP account settings"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do i get my salary in the account?"

Keyphrases:
2256it [1:16:33,  2.73s/it]
ChatCompletion(id='chatcmpl-9MzHgdqWz6PuStdQ3zXcDdnMJkGoj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary deposit", "receiving salary", "direct deposit setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715265820, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["salary deposit", "receiving salary", "direct deposit setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the ways for others to transfer me money?"

Keyphrases:
2257it [1:16:35,  2.36s/it]
ChatCompletion(id='chatcmpl-9MzHk07K4qiZrLhKbMmogiN1GPC83', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["receiving money", "transfer methods", "money transfer options"]', role='assistant', function_call=None, tool_calls=None))], created=1715265824, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["receiving money", "transfer methods", "money transfer options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What different ways are there for someone to send me money?"

Keyphrases:
2258it [1:16:40,  3.10s/it]
ChatCompletion(id='chatcmpl-9MzHlUeNs4ysnbnhQrkPx1B3pARz0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer options", "sending money methods", "receive money"]', role='assistant', function_call=None, tool_calls=None))], created=1715265825, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["money transfer options", "sending money methods", "receive money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I need to do to transfer my paycheck to my account?"

Keyphrases:
2259it [1:16:41,  2.57s/it]
ChatCompletion(id='chatcmpl-9MzHqBYD6HEniEKujozzA8XCOjWUA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["paycheck deposit", "set up direct deposit", "transfer paycheck to bank account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265830, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=232, total_tokens=250))
["paycheck deposit", "set up direct deposit", "transfer paycheck to bank account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can my friend send me money?"

Keyphrases:
2260it [1:16:43,  2.32s/it]
ChatCompletion(id='chatcmpl-9MzHrh7SMnODUMXoijpbBnOziVEYG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["send money", "receive money", "peer-to-peer transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265831, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["send money", "receive money", "peer-to-peer transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I directly transfer my salary onto here?"

Keyphrases:
2261it [1:16:45,  2.18s/it]
ChatCompletion(id='chatcmpl-9MzHtzIvSjYCodIYlWLgvTsRUIMrv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary transfer", "direct deposit setup", "setting up payroll transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265833, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["salary transfer", "direct deposit setup", "setting up payroll transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can this be used to receive my salary?"

Keyphrases:
2262it [1:16:50,  3.10s/it]
ChatCompletion(id='chatcmpl-9MzHvOdSX6qeDEUVorgqWvsgScGYY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary deposit", "receiving salary", "direct deposit eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715265835, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["salary deposit", "receiving salary", "direct deposit eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to deposit money in GBP?"

Keyphrases:
2263it [1:16:51,  2.59s/it]
ChatCompletion(id='chatcmpl-9MzI0BeZkbpXSsZnoqS3fRmMjzAnA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency deposit", "GBP deposit", "deposit options"]', role='assistant', function_call=None, tool_calls=None))], created=1715265840, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["currency deposit", "GBP deposit", "deposit options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I received my salary in GBP. How do I change this to my currency?"

Keyphrases:
2264it [1:16:53,  2.33s/it]
ChatCompletion(id='chatcmpl-9MzI1N9RXtNe3Tgn5yZwVLoapGfg9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "convert currency", "salary conversion"]', role='assistant', function_call=None, tool_calls=None))], created=1715265841, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=12, prompt_tokens=234, total_tokens=246))
["currency exchange", "convert currency", "salary conversion"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can my friend transfer money to me?"

Keyphrases:
2265it [1:16:55,  2.13s/it]
ChatCompletion(id='chatcmpl-9MzI3aRWDi0g6RNTVMmMsxN3sZKqU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer to account", "receiving transfer", "how to receive money"]', role='assistant', function_call=None, tool_calls=None))], created=1715265843, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=227, total_tokens=244))
["money transfer to account", "receiving transfer", "how to receive money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can my friends send me money?"

Keyphrases:
2266it [1:16:57,  2.13s/it]
ChatCompletion(id='chatcmpl-9MzI5dktiUA2fxSXh1N9yxNOnIsBA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer to account", "receiving money", "peer-to-peer transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265845, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=225, total_tokens=242))
["money transfer to account", "receiving money", "peer-to-peer transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I deposit my paycheck to this account?"

Keyphrases:
2267it [1:16:59,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzI71x2O6i7D4YjulrvRvhitEFp9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit paycheck", "account deposit", "salary deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715265847, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["deposit paycheck", "account deposit", "salary deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use this account to receive my salary?"

Keyphrases:
2268it [1:17:00,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzI9xXvs3pyb0IA4Fkn4peqxx4QR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary account", "receive salary", "direct deposit eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715265849, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["salary account", "receive salary", "direct deposit eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can i deposit my salary to this account?"

Keyphrases:
2269it [1:17:02,  1.81s/it]
ChatCompletion(id='chatcmpl-9MzIBGrNxNZSgYh0TuJYYo2jebfep', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary deposit", "direct deposit setup", "deposit paycheck"]', role='assistant', function_call=None, tool_calls=None))], created=1715265851, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["salary deposit", "direct deposit setup", "deposit paycheck"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I get my salary through this account?"

Keyphrases:
2270it [1:17:03,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzICGiPDxcRdCAYLVbJyso6onKcI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary deposit", "direct deposit setup", "receive salary"]', role='assistant', function_call=None, tool_calls=None))], created=1715265852, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["salary deposit", "direct deposit setup", "receive salary"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What if I need my salary in a different currency?"

Keyphrases:
2271it [1:17:05,  1.54s/it]
ChatCompletion(id='chatcmpl-9MzIEshvl9HhRicnouvJ3zRgwFgAo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "salary conversion"]', role='assistant', function_call=None, tool_calls=None))], created=1715265854, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=8, prompt_tokens=229, total_tokens=237))
["currency exchange", "salary conversion"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I receive my salary in GBP. Do I need to configure this somehwere?"

Keyphrases:
2272it [1:17:06,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzIFffiEJczc32bWJsZtLu1HGxNw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary configuration", "currency setting", "GBP account setting"]', role='assistant', function_call=None, tool_calls=None))], created=1715265855, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=235, total_tokens=248))
["salary configuration", "currency setting", "GBP account setting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you know if I can use this for my salary?"

Keyphrases:
2273it [1:17:08,  1.59s/it]
ChatCompletion(id='chatcmpl-9MzIH7oxkmKtAmmMLqxVhwMkF9Xud', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary deposit", "account usage", "salary account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265857, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["salary deposit", "account usage", "salary account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I get my paycheck through this?"

Keyphrases:
2274it [1:17:09,  1.54s/it]
ChatCompletion(id='chatcmpl-9MzIIHWqyx9mrhwb7b7OqAHBJW3Tx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["direct deposit setup", "receiving salary", "paycheck deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715265858, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["direct deposit setup", "receiving salary", "paycheck deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "can I transfer my salary if it's in a different currency?"

Keyphrases:
2275it [1:17:11,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzIKp7raKDrhxLQelgFSpGVRhL0r', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency transfer", "salary transfer", "international transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265860, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["currency transfer", "salary transfer", "international transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get paid in a different currency?"

Keyphrases:
2276it [1:17:14,  2.08s/it]
ChatCompletion(id='chatcmpl-9MzIMz8suCXbjEcNipGW37i9FqPaA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign currency payment", "currency exchange", "alternate currency payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715265862, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["foreign currency payment", "currency exchange", "alternate currency payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is my salary eligible for this?"

Keyphrases:
2277it [1:17:17,  2.13s/it]
ChatCompletion(id='chatcmpl-9MzIP9O11onKDh9RfDq3Ih1ou5cdE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["salary eligibility", "account qualification", "wage requirements"]', role='assistant', function_call=None, tool_calls=None))], created=1715265865, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["salary eligibility", "account qualification", "wage requirements"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My salary is in GBP; how can I note this in the app?"

Keyphrases:
2278it [1:17:18,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzIRCz6B9IVbXtgeiIz8297vXoh6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency setting", "update salary currency", "GBP salary"]', role='assistant', function_call=None, tool_calls=None))], created=1715265867, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["currency setting", "update salary currency", "GBP salary"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get paid in another currency?"

Keyphrases:
2279it [1:17:20,  1.89s/it]
ChatCompletion(id='chatcmpl-9MzISiFdFVVQkznBdz68zsQVamFnz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign currency payments", "currency exchange", "alternative currency options"]', role='assistant', function_call=None, tool_calls=None))], created=1715265868, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["foreign currency payments", "currency exchange", "alternative currency options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get my paycheck through here?"

Keyphrases:
2280it [1:17:22,  2.08s/it]
ChatCompletion(id='chatcmpl-9MzIUYEwPdNwlhYgF9LK2m0RgW0Us', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["direct deposit", "paycheck deposit", "receive salary"]', role='assistant', function_call=None, tool_calls=None))], created=1715265870, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["direct deposit", "paycheck deposit", "receive salary"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "dont understand why transfer failed"

Keyphrases:
2281it [1:17:24,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzIXz775tVwOvHtQuaqnjT6sD6n3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer explanation", "transfer troubleshooting"]', role='assistant', function_call=None, tool_calls=None))], created=1715265873, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["transfer issue", "failed transfer explanation", "transfer troubleshooting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please help me make a transfer. I keep receiving an error and I'm trying to make the initial mortgage payment for a flat I'm buying. What is the deal here?"

Keyphrases:
2282it [1:17:25,  1.77s/it]
ChatCompletion(id='chatcmpl-9MzIYqNA7C6fMGHWSS4nSpdiNiv2d', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer assistance", "error resolution", "mortgage payment issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715265874, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=253, total_tokens=267))
["transfer assistance", "error resolution", "mortgage payment issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer didn't work"

Keyphrases:
2283it [1:17:27,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzIZSkPiLaT8EsxmFJ0FctgPgkRI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer", "transaction problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265875, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["transfer issue", "failed transfer", "transaction problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Fix your system. I can't make transfers, I've tried like 5 times already."

Keyphrases:
2284it [1:17:29,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzIbSlNQzvhkCQY5kiyU2tWhi7sg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issues", "failed transfers", "system errors"]', role='assistant', function_call=None, tool_calls=None))], created=1715265877, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=237, total_tokens=249))
["transfer issues", "failed transfers", "system errors"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Tell me why my transfer failed!"

Keyphrases:
2285it [1:17:32,  2.26s/it]
ChatCompletion(id='chatcmpl-9MzId6zSrB2OwvYzqTGaN9seUzfC5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failure reason", "transfer status"]', role='assistant', function_call=None, tool_calls=None))], created=1715265879, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["transfer issue", "failure reason", "transfer status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer did not go through."

Keyphrases:
2286it [1:17:33,  1.98s/it]
ChatCompletion(id='chatcmpl-9MzIglBrtzxn6sG5tIX0DiL2XbeRP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer", "transfer not processed"]', role='assistant', function_call=None, tool_calls=None))], created=1715265882, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["transfer issue", "failed transfer", "transfer not processed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I not able to complete a transfer?"

Keyphrases:
2287it [1:17:35,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzIiqKFJjhFcJyWLfjseiLZpUdQX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transaction", "incomplete transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265884, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["transfer issue", "failed transaction", "incomplete transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you help me figure out what's happening? I'm trying to transfer money to a friend but it keeps getting returned. I'm not sure what i'm doing wrong."

Keyphrases:
2288it [1:17:36,  1.75s/it]
ChatCompletion(id='chatcmpl-9MzIjGvpqc99lnPoOkP03SQxR5PqD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer issues", "transfer failure", "problem sending money"]', role='assistant', function_call=None, tool_calls=None))], created=1715265885, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=253, total_tokens=267))
["money transfer issues", "transfer failure", "problem sending money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did my transfer not go through?"

Keyphrases:
2289it [1:17:40,  2.17s/it]
ChatCompletion(id='chatcmpl-9MzImSZHZp1qkmivG6bnfDbONrYH4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer", "transaction problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265888, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["transfer issue", "failed transfer", "transaction problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer didn't go through."

Keyphrases:
2290it [1:17:41,  1.89s/it]
ChatCompletion(id='chatcmpl-9MzIoScCDzJhumjASZnDfyayufEQy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer", "transfer not completed"]', role='assistant', function_call=None, tool_calls=None))], created=1715265890, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["transfer issue", "failed transfer", "transfer not completed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I could not get my transfer to happen correctly and was wondering why?"

Keyphrases:
2291it [1:17:42,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzIp8Jd8nTtJAZwp0QRWnCcbs3WX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer", "transfer problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265891, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["transfer issue", "failed transfer", "transfer problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how come my transfer didn't work"

Keyphrases:
2292it [1:17:43,  1.56s/it]
ChatCompletion(id='chatcmpl-9MzIqvAU2E5Vzm1BCG9wiTD0nhWF9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer", "transfer not successful"]', role='assistant', function_call=None, tool_calls=None))], created=1715265892, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["transfer issue", "failed transfer", "transfer not successful"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I transferred my funds, why did it not go through?"

Keyphrases:
2293it [1:17:45,  1.52s/it]
ChatCompletion(id='chatcmpl-9MzIsmX46SL2sLLGtyS7Gn6E5YFKg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["funds transfer issue", "transfer not completed", "failed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265894, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["funds transfer issue", "transfer not completed", "failed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why has my transfer failed?"

Keyphrases:
2294it [1:17:46,  1.49s/it]
ChatCompletion(id='chatcmpl-9MzIttopqElnvJ3GRVymaOVc5Zdkw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transaction", "transfer not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715265895, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["transfer issue", "failed transaction", "transfer not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did my transfer fail?"

Keyphrases:
2295it [1:17:48,  1.48s/it]
ChatCompletion(id='chatcmpl-9MzIuRfX1jz3UJlwrFG9Sy3UPRWES', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer reason", "transfer failure explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715265896, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["transfer issue", "failed transfer reason", "transfer failure explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why hasn't my transfer been made?"

Keyphrases:
2296it [1:17:49,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzIwThYRrhbOTV2QfvUQ9q5jMZoj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer status", "pending transfer", "transfer not completed"]', role='assistant', function_call=None, tool_calls=None))], created=1715265898, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["transfer status", "pending transfer", "transfer not completed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer will not go through."

Keyphrases:
2297it [1:17:51,  1.58s/it]
ChatCompletion(id='chatcmpl-9MzIxZhcQcsNIvlMZwsWS2TbLIvZJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transaction", "transaction not processed"]', role='assistant', function_call=None, tool_calls=None))], created=1715265899, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["transfer issue", "failed transaction", "transaction not processed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer keeps failing and I just want to transfer the money can you please make it work?"

Keyphrases:
2298it [1:17:52,  1.57s/it]
ChatCompletion(id='chatcmpl-9MzIz4dUuam10I1LcDQ7I8V6w60Ss', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer resolution", "transfer assistance"]', role='assistant', function_call=None, tool_calls=None))], created=1715265901, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=237, total_tokens=250))
["transfer issue", "failed transfer resolution", "transfer assistance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The transfer keeps failing , I tried to transfer some money to friends this morning but it keeps getting rejected for some reason, Would you please check the issue ?"

Keyphrases:
2299it [1:17:54,  1.52s/it]
ChatCompletion(id='chatcmpl-9MzJ1SkjGh1gqk8y8dy0E5lKBc3IH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "money transfer failure", "rejected transfer", "transfer assistance"]', role='assistant', function_call=None, tool_calls=None))], created=1715265903, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=250, total_tokens=267))
["transfer issue", "money transfer failure", "rejected transfer", "transfer assistance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why would a transfer fail?"

Keyphrases:
2300it [1:17:56,  1.82s/it]
ChatCompletion(id='chatcmpl-9MzJ2m1sptwECW3Y5jDPQ8obpiDrU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["failed transfer reasons", "transfer issues", "why transfer not successful"]', role='assistant', function_call=None, tool_calls=None))], created=1715265904, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["failed transfer reasons", "transfer issues", "why transfer not successful"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are your policies for card transfers?"

Keyphrases:
2301it [1:17:58,  1.84s/it]
ChatCompletion(id='chatcmpl-9MzJ5uSmRW5Y8fhAEdndYdacGlSPq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card transfer policies", "transfer guidelines", "banking regulations for transfers"]', role='assistant', function_call=None, tool_calls=None))], created=1715265907, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["card transfer policies", "transfer guidelines", "banking regulations for transfers"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is the system down? I've been trying to do a transfer and have failed?"

Keyphrases:
2302it [1:18:00,  1.75s/it]
ChatCompletion(id='chatcmpl-9MzJ6J8L2Vfrv0o8AZVBhO2ND0Gog', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["system status", "transfer issue", "online banking downtime"]', role='assistant', function_call=None, tool_calls=None))], created=1715265908, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=235, total_tokens=248))
["system status", "transfer issue", "online banking downtime"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to make a transfer but it failed"

Keyphrases:
2303it [1:18:02,  1.75s/it]
ChatCompletion(id='chatcmpl-9MzJ8DbdWSpID179RdMtOTWIdqefo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["failed transfer", "transfer issue", "transaction problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265910, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["failed transfer", "transfer issue", "transaction problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why couldn't I complete a transfer?"

Keyphrases:
2304it [1:18:03,  1.78s/it]
ChatCompletion(id='chatcmpl-9MzJAHeQpbh6nB79v4hsHNVqDKaHW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transaction", "incomplete transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265912, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["transfer issue", "failed transaction", "incomplete transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer appeared not to work."

Keyphrases:
2305it [1:18:05,  1.70s/it]
ChatCompletion(id='chatcmpl-9MzJCOXTnG8i54R87ML0Yipw01CLl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer", "transfer not successful"]', role='assistant', function_call=None, tool_calls=None))], created=1715265914, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["transfer issue", "failed transfer", "transfer not successful"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is stopping my money from transferring?"

Keyphrases:
2306it [1:18:06,  1.53s/it]
ChatCompletion(id='chatcmpl-9MzJDdzSAu1pv0cBQGa7n60FwFKFe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "blocked transfer", "money transfer problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265915, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["transfer issue", "blocked transfer", "money transfer problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hi, I'm buying a flat and I'm trying to get my mortgage to go though. Every time I check I simply get an error message. Is there any way you can help me get this money transferred over. Thanks!"

Keyphrases:
2307it [1:18:27,  7.27s/it]
ChatCompletion(id='chatcmpl-9MzJFFJgAbPawlhZs3ju2FdYFNcP4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["mortgage transfer", "error message", "transfer money for mortgage"]', role='assistant', function_call=None, tool_calls=None))], created=1715265917, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=264, total_tokens=279))
["mortgage transfer", "error message", "transfer money for mortgage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My attempted transfer failed."

Keyphrases:
2308it [1:18:29,  5.90s/it]
ChatCompletion(id='chatcmpl-9MzJZNJgIFtkDStv7M1l5Xh9PpKvz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["failed transfer", "transfer issue", "transfer not completed"]', role='assistant', function_call=None, tool_calls=None))], created=1715265937, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["failed transfer", "transfer issue", "transfer not completed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can not seem to make a successful transfer, can you tell me what I'm doing wrong?"

Keyphrases:
2309it [1:18:31,  4.62s/it]
ChatCompletion(id='chatcmpl-9MzJcXQg88q9HLBgIrBHLMOrB67Ur', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issues", "failed transfer", "troubleshoot transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265940, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=238, total_tokens=252))
["transfer issues", "failed transfer", "troubleshoot transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please help me as i am continuously facing the issue in transferring money to my friends, as all my transactions are getting failed."

Keyphrases:
2310it [1:18:34,  4.12s/it]
ChatCompletion(id='chatcmpl-9MzJd4llPJaZzkcxTjq6q7jQJOsq2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer issue", "failed transactions", "transaction problems"]', role='assistant', function_call=None, tool_calls=None))], created=1715265941, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=243, total_tokens=256))
["money transfer issue", "failed transactions", "transaction problems"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am trying to make a transfer and am unsuccessful, can you please tell me why?"

Keyphrases:
2311it [1:18:35,  3.32s/it]
ChatCompletion(id='chatcmpl-9MzJgRlk4nTPpMZGE8PLWkArpLkQn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issues", "failed transfer", "help with transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265944, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=236, total_tokens=249))
["transfer issues", "failed transfer", "help with transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer did not seem to work."

Keyphrases:
2312it [1:18:39,  3.52s/it]
ChatCompletion(id='chatcmpl-9MzJiiBYivmvZEoGcC44mGZdLJWN3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["failed transfer", "transfer not successful", "transfer issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715265946, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["failed transfer", "transfer not successful", "transfer issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've now been trying to do a really standard transfer 5 times already. What's going on, is your system broken or something?!"

Keyphrases:
2313it [1:18:41,  2.86s/it]
ChatCompletion(id='chatcmpl-9MzJmkgIIQOGh7DcitDORkFlg3VZK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issues", "system error", "failed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265950, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=247, total_tokens=259))
["transfer issues", "system error", "failed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "help me with my transfer"

Keyphrases:
2314it [1:18:44,  2.99s/it]
ChatCompletion(id='chatcmpl-9MzJn0FGfUQ9m3APU309aykOr6XhM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer assistance", "transfer help", "support with transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265951, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["transfer assistance", "transfer help", "support with transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Says my transfer can't be completed?"

Keyphrases:
2315it [1:18:45,  2.46s/it]
ChatCompletion(id='chatcmpl-9MzJqaxpNClqmMQTugpYGRkyYTDfc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "transfer not completed", "failed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265954, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["transfer issue", "transfer not completed", "failed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "can you tell me why my transfer failed?"

Keyphrases:
2316it [1:18:47,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzJsY4H8hKqPKpC2fNiKYLCe9vUQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer reason", "transfer not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715265956, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["transfer issue", "failed transfer reason", "transfer not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why didn't my transfer go through?"

Keyphrases:
2317it [1:18:48,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzJtahzaRPSUbyS6ZavxavVf1zwb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transfer", "transaction problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715265957, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["transfer issue", "failed transfer", "transaction problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've attempted to do a very standard transfer and have tried 5 times at this point. Can you tell me what the issue is? Is the system down?"

Keyphrases:
2318it [1:18:49,  1.77s/it]
ChatCompletion(id='chatcmpl-9MzJugmDjUJaBRjKj5EKt4qOVWpfN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "failed transaction", "system status"]', role='assistant', function_call=None, tool_calls=None))], created=1715265958, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=251, total_tokens=263))
["transfer issue", "failed transaction", "system status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you provide a reason as to why my transfer did not work?"

Keyphrases:
2319it [1:18:52,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzJwMoxWlYG9CqGSL3jsdkHNxecT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "reason for transfer failure", "transfer problem explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715265960, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["transfer issue", "reason for transfer failure", "transfer problem explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to transfer money and it did not work."

Keyphrases:
2320it [1:18:55,  2.30s/it]
ChatCompletion(id='chatcmpl-9MzJyXDI38JsDjHmgnOinLsGb30FR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["failed money transfer", "transfer issue", "unsuccessful transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715265962, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["failed money transfer", "transfer issue", "unsuccessful transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I do a bank transfer to put additional money in my account because I am out of money?"

Keyphrases:
2321it [1:18:56,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzK1Xi81ySC3Lyuz2vdSfPjpiLa6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bank transfer", "deposit money", "add funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715265965, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=238, total_tokens=250))
["bank transfer", "deposit money", "add funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm out of money, can I add money with my bank?"

Keyphrases:
2322it [1:18:57,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzK37npROBmoCAfB9DdksjzDHeN8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["add money", "bank deposit", "fund account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265967, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=232, total_tokens=244))
["add money", "bank deposit", "fund account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I go forth on transferring money into my account?"

Keyphrases:
2323it [1:19:00,  1.90s/it]
ChatCompletion(id='chatcmpl-9MzK4zesl7EOLEaaqCN0yOeroDvmf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "deposit funds", "add money to account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265968, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["money transfer", "deposit funds", "add money to account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't understand how to top up my account, can you please explain the process?"

Keyphrases:
2324it [1:19:03,  2.42s/it]
ChatCompletion(id='chatcmpl-9MzK6n3z1L1qvApIBT6OzT215SJ9G', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account top-up", "top-up process", "how to deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715265970, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["account top-up", "top-up process", "how to deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't understand the money transfer process."

Keyphrases:
2325it [1:19:05,  2.23s/it]
ChatCompletion(id='chatcmpl-9MzKAn0oMaWsN4xAoFyju732jjQdl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer process", "transfer explanation", "how to transfer money"]', role='assistant', function_call=None, tool_calls=None))], created=1715265974, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["money transfer process", "transfer explanation", "how to transfer money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to transfer money into my account, how do I go about doing this?"

Keyphrases:
2326it [1:19:07,  2.05s/it]
ChatCompletion(id='chatcmpl-9MzKBfSzV6ewykk7ZuHC8bAmknQPE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "deposit funds", "transfer to own account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265975, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["money transfer", "deposit funds", "transfer to own account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I need to do to transfer money into my account?"

Keyphrases:
2327it [1:19:09,  2.03s/it]
ChatCompletion(id='chatcmpl-9MzKD8KutFYF7P0q3n4V9NiIwHpJl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "deposit funds", "transfer to own account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265977, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["money transfer", "deposit funds", "transfer to own account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't know what to do. Should I transfer funds. My account is out of money."

Keyphrases:
2328it [1:19:10,  1.87s/it]
ChatCompletion(id='chatcmpl-9MzKFjEZEuzEe9o3zZV5nsVQeGUV2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer advice", "low balance", "transfer funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715265979, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=238, total_tokens=251))
["fund transfer advice", "low balance", "transfer funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I add funds to the card directly from my bank account?"

Keyphrases:
2329it [1:19:11,  1.63s/it]
ChatCompletion(id='chatcmpl-9MzKGoiuGC9uadSXMBoXGQGFHa8WO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["add funds", "bank transfer to card", "direct deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715265980, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["add funds", "bank transfer to card", "direct deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How does tranferring money into my account work?"

Keyphrases:
2330it [1:19:13,  1.70s/it]
ChatCompletion(id='chatcmpl-9MzKImad7fsIeDg16ai5SlmYRVd43', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer process", "how to transfer money", "bank transfer instructions"]', role='assistant', function_call=None, tool_calls=None))], created=1715265982, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["money transfer process", "how to transfer money", "bank transfer instructions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I NEED TO KNOW HOW TO TRANSFER MONEY INTO MY BANK ACCOUNT. PLEASE HELP"

Keyphrases:
2331it [1:19:15,  1.85s/it]
ChatCompletion(id='chatcmpl-9MzKJDMZEB8qr7rHNH5sN21oLrNzi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "deposit into account", "bank transfer instructions"]', role='assistant', function_call=None, tool_calls=None))], created=1715265983, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["money transfer", "deposit into account", "bank transfer instructions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to transfer some money from my other bank account into this one."

Keyphrases:
2332it [1:19:18,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzKMWDg6qTjGYEsIy5cm7b3UorJV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "interbank transfer", "transfer money into account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265986, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["money transfer", "interbank transfer", "transfer money into account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When I want to transfer money to my account, how can I do that?"

Keyphrases:
2333it [1:19:21,  2.40s/it]
ChatCompletion(id='chatcmpl-9MzKOY2QY9iP8jl95PCnrCjCF533X', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "transfer to own account", "how to transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715265988, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["money transfer", "transfer to own account", "how to transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to transfer funds into my account. How can I do this?"

Keyphrases:
2334it [1:19:24,  2.51s/it]
ChatCompletion(id='chatcmpl-9MzKRWLzc307aaiiIPpN0oJR4nhNl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer", "deposit funds", "transfer into account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265991, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["fund transfer", "deposit funds", "transfer into account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the steps I follow to transfer money into my account?"

Keyphrases:
2335it [1:19:26,  2.34s/it]
ChatCompletion(id='chatcmpl-9MzKUVV6btNvEnfnuP7KIktNQERQZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer process", "transfer steps", "account funding"]', role='assistant', function_call=None, tool_calls=None))], created=1715265994, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["money transfer process", "transfer steps", "account funding"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I transfer funds from my bank to my top up account?"

Keyphrases:
2336it [1:19:28,  2.16s/it]
ChatCompletion(id='chatcmpl-9MzKWkdaG0ohS0qtbRmSZR6XMv20C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer", "bank to top up account", "move money"]', role='assistant', function_call=None, tool_calls=None))], created=1715265996, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["fund transfer", "bank to top up account", "move money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to top my account by using a bank transfer. How would that work?"

Keyphrases:
2337it [1:19:29,  1.96s/it]
ChatCompletion(id='chatcmpl-9MzKYehR0mjtw5otd1SMHK3uCTFh3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bank transfer top-up", "account funding", "using bank transfer for top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715265998, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=235, total_tokens=253))
["bank transfer top-up", "account funding", "using bank transfer for top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How to I transfer my funds into my account?"

Keyphrases:
2338it [1:19:31,  1.89s/it]
ChatCompletion(id='chatcmpl-9MzKZUZqoXqClFPNqZ7gLsSMyqeJx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer", "account deposit", "transfer money to account"]', role='assistant', function_call=None, tool_calls=None))], created=1715265999, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["fund transfer", "account deposit", "transfer money to account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I top up my card?"

Keyphrases:
2339it [1:19:32,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzKbi6jNErvY6krgSwaK8qk5hvK4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card top-up", "add money to card", "recharge card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266001, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["card top-up", "add money to card", "recharge card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I transfer money from an outside bank?"

Keyphrases:
2340it [1:19:35,  1.95s/it]
ChatCompletion(id='chatcmpl-9MzKdIp18hQwVzGJIjr4RLJwGDTEJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["external transfer", "money transfer from another bank", "transfer money to my account"]', role='assistant', function_call=None, tool_calls=None))], created=1715266003, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=228, total_tokens=246))
["external transfer", "money transfer from another bank", "transfer money to my account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I fund my top-up account using my bank account?"

Keyphrases:
2341it [1:19:37,  1.92s/it]
ChatCompletion(id='chatcmpl-9MzKflodlYaHCSgReKMny4erPPX9v', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account funding", "top-up via bank account", "bank transfer to account"]', role='assistant', function_call=None, tool_calls=None))], created=1715266005, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["account funding", "top-up via bank account", "bank transfer to account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What methods can I use to add money to my account?"

Keyphrases:
2342it [1:19:38,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzKhlKDpThWHKnwrY72a2rg3ltRz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["funding methods", "add money", "deposit options"]', role='assistant', function_call=None, tool_calls=None))], created=1715266007, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["funding methods", "add money", "deposit options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to use the bank transfer feature, but I can't find it. Can you please give me the details?"

Keyphrases:
2343it [1:19:40,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzKiOISfe7NWexVYiSZl9D1972Mf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bank transfer", "transfer feature access", "how to use bank transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266008, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=243, total_tokens=259))
["bank transfer", "transfer feature access", "how to use bank transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I perform a dual money transferring from one account to another?"

Keyphrases:
2344it [1:19:41,  1.58s/it]
ChatCompletion(id='chatcmpl-9MzKknvFNtINNPrNLfAeVnZNplrdp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["dual transfer", "money transferring", "account to account transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266010, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["dual transfer", "money transferring", "account to account transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "CAN YOU EXPLAIN HOW TO TRANSFER MONEY INTO MY  ACCOUNT FOR ME?"

Keyphrases:
2345it [1:19:44,  2.06s/it]
ChatCompletion(id='chatcmpl-9MzKl75AD1YvQLtUPMq0Kjx5vA0zR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer instructions", "how to transfer money", "bank transfer guidance"]', role='assistant', function_call=None, tool_calls=None))], created=1715266011, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=234, total_tokens=250))
["money transfer instructions", "how to transfer money", "bank transfer guidance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to bank account transfer from another account into this one, what is the easiest way that can be done, and what information do i need?"

Keyphrases:
2346it [1:19:45,  1.84s/it]
ChatCompletion(id='chatcmpl-9MzKotyHaTG7toVrnimr3QVSobBYv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account transfer", "transfer requirements", "how to transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266014, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=248, total_tokens=261))
["account transfer", "transfer requirements", "how to transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I transfer money to my account?"

Keyphrases:
2347it [1:19:47,  1.64s/it]
ChatCompletion(id='chatcmpl-9MzKqRhvfhYf7JMAKYrD9D1sUctDS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "account funding", "send money"]', role='assistant', function_call=None, tool_calls=None))], created=1715266016, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["money transfer", "account funding", "send money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I send my account money through transfer?"

Keyphrases:
2348it [1:19:48,  1.50s/it]
ChatCompletion(id='chatcmpl-9MzKr5TnbaB2B8z8IgRwlcIYslmVJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "send money", "account transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266017, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["money transfer", "send money", "account transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I do an international transfer?"

Keyphrases:
2349it [1:19:49,  1.51s/it]
ChatCompletion(id='chatcmpl-9MzKshIO30qy6ksrIUnvUP0VhtUk8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international transfer", "send money abroad", "overseas money transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266018, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["international transfer", "send money abroad", "overseas money transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there ways to transfer money into my account?"

Keyphrases:
2350it [1:19:51,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzKuRJ3pcFPVU7DFyfTPt175F6xR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "deposit options", "add funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715266020, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["money transfer", "deposit options", "add funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to transfer from accounts in order to Top up. What are the steps necessary."

Keyphrases:
2351it [1:19:52,  1.42s/it]
ChatCompletion(id='chatcmpl-9MzKvdevZY1DmsY2XZzU8lT0hLPz8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account transfer", "top up steps", "transfer procedure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266021, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=236, total_tokens=249))
["account transfer", "top up steps", "transfer procedure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How does a transfer work?"

Keyphrases:
2352it [1:19:53,  1.42s/it]
ChatCompletion(id='chatcmpl-9MzKweibAbmUQqZ6CdFqdhjszcPj4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer process", "how to transfer", "transfer instructions"]', role='assistant', function_call=None, tool_calls=None))], created=1715266022, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["transfer process", "how to transfer", "transfer instructions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like use the bank transfer, but I don't understand the process, can you please explain, topping up?"

Keyphrases:
2353it [1:19:55,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzKyLIwMgdiTDM9Y4oD6TpRlvnXi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bank transfer", "transfer process explanation", "how to top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266024, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=242, total_tokens=257))
["bank transfer", "transfer process explanation", "how to top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to use bank transfer for topping up my account. How is it handled?"

Keyphrases:
2354it [1:19:56,  1.48s/it]
ChatCompletion(id='chatcmpl-9MzKzK5GYcxoOALtcwuqBqa53E8kV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bank transfer", "account top-up", "top-up method"]', role='assistant', function_call=None, tool_calls=None))], created=1715266025, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["bank transfer", "account top-up", "top-up method"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I checked my account today and it said I was out of money. How do I transfer money into my account?"

Keyphrases:
2355it [1:19:58,  1.44s/it]
ChatCompletion(id='chatcmpl-9MzL19MS1M5S8bsHtSjLmkOApyai0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account top-up", "transfer money to account", "funds transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266027, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=241, total_tokens=257))
["account top-up", "transfer money to account", "funds transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I transfer money to my account?"

Keyphrases:
2356it [1:20:00,  1.55s/it]
ChatCompletion(id='chatcmpl-9MzL2ovqKVJl92gbezivbPlJQjudV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "send money", "account deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715266028, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["money transfer", "send money", "account deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to transfer funds from one account to another."

Keyphrases:
2357it [1:20:01,  1.50s/it]
ChatCompletion(id='chatcmpl-9MzL4k2zCJL7js83K3lDDDj7VMhCK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer", "account to account transfer", "sending money"]', role='assistant', function_call=None, tool_calls=None))], created=1715266030, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["fund transfer", "account to account transfer", "sending money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm trying to transfer money into my account."

Keyphrases:
2358it [1:20:03,  1.60s/it]
ChatCompletion(id='chatcmpl-9MzL5M3tqclf82zkF9ycPhbjAAv0C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer", "deposit funds", "incoming transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266031, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["money transfer", "deposit funds", "incoming transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to transfer money from my other bank account into this one."

Keyphrases:
2359it [1:20:05,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzL7aW5d6Mx8jYxedHBKuJRCK95o', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["fund transfer", "money transfer", "interbank transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266033, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["fund transfer", "money transfer", "interbank transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use a bank transfer to refill my account?"

Keyphrases:
2360it [1:20:07,  1.79s/it]
ChatCompletion(id='chatcmpl-9MzL9hvoUmL4HBporIrfFL8xXcyWB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bank transfer", "account refill", "fund account via transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266035, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["bank transfer", "account refill", "fund account via transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What all is needed to verify the top-up card?"

Keyphrases:
2361it [1:20:09,  2.02s/it]
ChatCompletion(id='chatcmpl-9MzLBX0vM7x1YXuZLU6CPNa7y545W', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card verification", "top-up card requirements", "verification documents"]', role='assistant', function_call=None, tool_calls=None))], created=1715266037, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["card verification", "top-up card requirements", "verification documents"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It wants me to verify the top up. Why?"

Keyphrases:
2362it [1:20:11,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzLEGY2Bw1eYPuwxsJQsMUD1CGCs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verify top up", "account verification", "top up confirmation"]', role='assistant', function_call=None, tool_calls=None))], created=1715266040, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["verify top up", "account verification", "top up confirmation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I find the top-up verification code?"

Keyphrases:
2363it [1:20:13,  1.90s/it]
ChatCompletion(id='chatcmpl-9MzLFvjAQhh86Y67fLv4bOybTBNXJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up code", "verification code", "find verification code"]', role='assistant', function_call=None, tool_calls=None))], created=1715266041, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top-up code", "verification code", "find verification code"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do I have to verify the top-up that I started?"

Keyphrases:
2364it [1:20:14,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzLH6OyAWI6XM9VeRLvJ5bCa28XP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up verification", "verify transaction", "transaction authentication"]', role='assistant', function_call=None, tool_calls=None))], created=1715266043, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["top-up verification", "verify transaction", "transaction authentication"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you give me information about verification code?"

Keyphrases:
2365it [1:20:16,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzLJCmYj458ODJyY789Yy6yrpM43', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification code", "security code information", "code details"]', role='assistant', function_call=None, tool_calls=None))], created=1715266045, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["verification code", "security code information", "code details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the benefits to verifying the top-up?"

Keyphrases:
2366it [1:20:19,  2.07s/it]
ChatCompletion(id='chatcmpl-9MzLKyBar6ICf4BRpqjcEap65Xhqg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up benefits", "verify top-up", "top-up verification advantages"]', role='assistant', function_call=None, tool_calls=None))], created=1715266046, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["top-up benefits", "verify top-up", "top-up verification advantages"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how come the verification with the top up"

Keyphrases:
2367it [1:20:20,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzLNJUKg5uS3LWtrfj7zefQNm2ki', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification issue", "top up problem", "account verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715266049, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["verification issue", "top up problem", "account verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I verify a top up?"

Keyphrases:
2368it [1:20:22,  1.80s/it]
ChatCompletion(id='chatcmpl-9MzLPJf2ZgM9CTFvDn3Zal7xb5XWl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up verification", "verify payment", "transaction verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715266051, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["top up verification", "verify payment", "transaction verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "reason i need to verify top up"

Keyphrases:
2369it [1:20:24,  1.75s/it]
ChatCompletion(id='chatcmpl-9MzLQRnmpQT3E3l70cuhI2cbTxtmJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification required", "top up verification", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715266052, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["verification required", "top up verification", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do you need code verification for my top up?"

Keyphrases:
2370it [1:20:26,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzLSt3U4ioSG4XEa5fjcYaH2aFvW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["code verification", "account security", "top up verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715266054, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["code verification", "account security", "top up verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I find the verification code on a top-up card?"

Keyphrases:
2371it [1:20:30,  2.58s/it]
ChatCompletion(id='chatcmpl-9MzLUhwYBi53SKH7rikDIzXdLoTlz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification code location", "top-up card code", "find verification code"]', role='assistant', function_call=None, tool_calls=None))], created=1715266056, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["verification code location", "top-up card code", "find verification code"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I get my top-up verification code?"

Keyphrases:
2372it [1:20:32,  2.49s/it]
ChatCompletion(id='chatcmpl-9MzLYAkAKxiKVKFNQdFefITJTsBzF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification code", "top-up code", "account verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715266060, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["verification code", "top-up code", "account verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to verify a top up?"

Keyphrases:
2373it [1:20:34,  2.26s/it]
ChatCompletion(id='chatcmpl-9MzLaUMr5doPIejQAyfR9bSSa0DEL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up verification", "verify transaction", "confirmation of top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266062, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["top up verification", "verify transaction", "confirmation of top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it normal to have to verify my top-up or is something wrong?"

Keyphrases:
2374it [1:20:35,  1.98s/it]
ChatCompletion(id='chatcmpl-9MzLcBaeodPjJfgN5cyyE7NKkCJ5K', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up verification", "account security", "verification requirement"]', role='assistant', function_call=None, tool_calls=None))], created=1715266064, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["top-up verification", "account security", "verification requirement"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why does the top-up need verification?"

Keyphrases:
2375it [1:20:37,  1.91s/it]
ChatCompletion(id='chatcmpl-9MzLeHmDCebRhOaBtqJ9eS0MCtoHe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up verification", "account verification requirement", "verification for deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715266066, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["top-up verification", "account verification requirement", "verification for deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why does top-up need verifying?"

Keyphrases:
2376it [1:20:39,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzLfHzt3bCEvyjZcWtqvbFIDSqpH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up verification", "verification required", "account top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266067, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["top-up verification", "verification required", "account top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it necessary to verify my top up?"

Keyphrases:
2377it [1:20:42,  2.28s/it]
ChatCompletion(id='chatcmpl-9MzLhP4WYht6EkorvwlavkOnURQuF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up verification", "verification requirement", "account top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266069, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["top up verification", "verification requirement", "account top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why am i to verify the top-ups?"

Keyphrases:
2378it [1:20:43,  1.96s/it]
ChatCompletion(id='chatcmpl-9MzLkbqn3eSO34xviyzB9HJz77OpF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification requirement", "top-up verification", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715266072, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["verification requirement", "top-up verification", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where's the verification code for the top-up card?"

Keyphrases:
2379it [1:20:45,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzLm8lpWraDkHh4W7pFnQtrcUuSb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification code", "top-up card code", "code not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715266074, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["verification code", "top-up card code", "code not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I find the verification code for my top-up card?"

Keyphrases:
2380it [1:20:46,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzLnHY6hYPH4Cbyw7n1l0eUukhMg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification code", "top-up card code", "find code"]', role='assistant', function_call=None, tool_calls=None))], created=1715266075, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["verification code", "top-up card code", "find code"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is it important to verify a top-up card?"

Keyphrases:
2381it [1:20:48,  1.62s/it]
ChatCompletion(id='chatcmpl-9MzLpztWQOSS2nsgWRV5xnURqE7QL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card verification", "importance of verification", "top-up card security"]', role='assistant', function_call=None, tool_calls=None))], created=1715266077, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["card verification", "importance of verification", "top-up card security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why do I have to verify the top-up?"

Keyphrases:
2382it [1:20:49,  1.62s/it]
ChatCompletion(id='chatcmpl-9MzLqVQvDdn5QWSWP2aOOFph7X0jU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up verification", "account security", "verify transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266078, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["top-up verification", "account security", "verify transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the verification code on a top-up?"

Keyphrases:
2383it [1:20:51,  1.54s/it]
ChatCompletion(id='chatcmpl-9MzLrec3pSS75n5UkuidwP2XQr7KT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification code", "top-up verification", "code for top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266079, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["verification code", "top-up verification", "code for top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't find the top-up verification code."

Keyphrases:
2384it [1:20:52,  1.63s/it]
ChatCompletion(id='chatcmpl-9MzLtCSCrj34DcP0Z7mLc9H76zUPT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up verification", "missing verification code", "code not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715266081, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["top-up verification", "missing verification code", "code not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I go forth verifying my top-up card?"

Keyphrases:
2385it [1:20:54,  1.53s/it]
ChatCompletion(id='chatcmpl-9MzLvoXk2Qw57nFvBm9UaRUOML8Qz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verify top-up card", "card verification process", "top-up card authentication"]', role='assistant', function_call=None, tool_calls=None))], created=1715266083, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["verify top-up card", "card verification process", "top-up card authentication"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I find the top-up verification code?"

Keyphrases:
2386it [1:20:56,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzLwpOwowBPiF892lPFBIrmFQ2oK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up code", "verification code", "top-up verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715266084, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top-up code", "verification code", "top-up verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How is the top-up card verified?"

Keyphrases:
2387it [1:20:57,  1.64s/it]
ChatCompletion(id='chatcmpl-9MzLyXhZw1dOUC5QsNbSZyRINmWu3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card verification", "top-up verification", "verify top-up card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266086, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["card verification", "top-up verification", "verify top-up card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a verification code for the top-up card?"

Keyphrases:
2388it [1:20:59,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzM0pioZkqwNBqIhopSRzQWj34ra', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification code", "top-up card security", "card authentication"]', role='assistant', function_call=None, tool_calls=None))], created=1715266088, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["verification code", "top-up card security", "card authentication"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the importance of verifying the top-up?"

Keyphrases:
2389it [1:21:00,  1.52s/it]
ChatCompletion(id='chatcmpl-9MzM189iUESclxb1Mh36o1EazJ446', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up verification", "verification reason", "verify top-up importance"]', role='assistant', function_call=None, tool_calls=None))], created=1715266089, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["top-up verification", "verification reason", "verify top-up importance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "help me find the top-up card's verification code?"

Keyphrases:
2390it [1:21:02,  1.52s/it]
ChatCompletion(id='chatcmpl-9MzM3Z5fQZKcfHM3Mk1PJk1dASvET', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification code", "top-up card code", "code retrieval"]', role='assistant', function_call=None, tool_calls=None))], created=1715266091, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["verification code", "top-up card code", "code retrieval"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't understand why it says I have to verify the top-up."

Keyphrases:
2391it [1:21:03,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzM4KFEcKZBZGNWSabJLLV2zaoNW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up verification", "account verification required", "verify top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266092, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["top-up verification", "account verification required", "verify top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I verify a top-up and what card is used?"

Keyphrases:
2392it [1:21:06,  1.99s/it]
ChatCompletion(id='chatcmpl-9MzM54gprZIS1VgIEhFkyNt7xlUDP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up verification", "card used for top-up", "verify payment method"]', role='assistant', function_call=None, tool_calls=None))], created=1715266093, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["top-up verification", "card used for top-up", "verify payment method"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I go to get the code to verify the top up card?"

Keyphrases:
2393it [1:21:10,  2.47s/it]
ChatCompletion(id='chatcmpl-9MzM94cSbskH8BX9OeM66pjSyD6Nk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up card code", "verification code", "code retrieval"]', role='assistant', function_call=None, tool_calls=None))], created=1715266097, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["top up card code", "verification code", "code retrieval"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The top-up verification code is missing"

Keyphrases:
2394it [1:21:12,  2.41s/it]
ChatCompletion(id='chatcmpl-9MzMC8EKAZa7Yg0oEayVRY9CW3fxf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing verification code", "top-up issue", "code not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715266100, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["missing verification code", "top-up issue", "code not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I verify a top-up?"

Keyphrases:
2395it [1:21:14,  2.21s/it]
ChatCompletion(id='chatcmpl-9MzMFtZAkKrLfybczP3qyEExbfBe4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verify top-up", "top-up confirmation", "confirm reload"]', role='assistant', function_call=None, tool_calls=None))], created=1715266103, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["verify top-up", "top-up confirmation", "confirm reload"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I cannot locate the verification code for my top-up card. Please help me."

Keyphrases:
2396it [1:21:15,  1.99s/it]
ChatCompletion(id='chatcmpl-9MzMG7sC62ngzKSCf9lLS5L2TkMWC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification code missing", "top-up card issue", "code retrieval"]', role='assistant', function_call=None, tool_calls=None))], created=1715266104, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["verification code missing", "top-up card issue", "code retrieval"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I find the top-up verification code?"

Keyphrases:
2397it [1:21:18,  2.26s/it]
ChatCompletion(id='chatcmpl-9MzMIJB8eTvkOmcJX1tXFD3TtOail', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up code", "verification code", "find verification code"]', role='assistant', function_call=None, tool_calls=None))], created=1715266106, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top-up code", "verification code", "find verification code"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need help finding the verification code for my top-up card."

Keyphrases:
2398it [1:21:20,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzMLx50mnRqBsB7aozsNS9Un6bpl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification code", "top-up card code", "card verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715266109, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["verification code", "top-up card code", "card verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a verification code for top-ups?"

Keyphrases:
2399it [1:21:21,  1.87s/it]
ChatCompletion(id='chatcmpl-9MzMMeGxqEPcNM9zi4oZaxo0iTHQq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["verification code", "top-up security", "account top-up verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715266110, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["verification code", "top-up security", "account top-up verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the necessity of verifying the top up?"

Keyphrases:
2400it [1:21:23,  1.70s/it]
ChatCompletion(id='chatcmpl-9MzMOb58ba3BbnGqjc70jEijM5b03', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up verification", "verification necessity", "account top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266112, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top up verification", "verification necessity", "account top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Would it be possible to get another card?"

Keyphrases:
2401it [1:21:25,  2.03s/it]
ChatCompletion(id='chatcmpl-9MzMPGaZ0UFpeDXWmMaTCZ696HFzb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request new card", "additional card", "card replacement"]', role='assistant', function_call=None, tool_calls=None))], created=1715266113, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["request new card", "additional card", "card replacement"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many cards can I have for one account?"

Keyphrases:
2402it [1:21:28,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzMSxo2oSE3ZRl5cpiimo21dXG1P', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple cards", "card limit", "account card limit"]', role='assistant', function_call=None, tool_calls=None))], created=1715266116, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["multiple cards", "card limit", "account card limit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to order another crad"

Keyphrases:
2403it [1:21:30,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzMUgLA4eDYoUKWfy3MUJwBj2AvR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["order new card", "replacement card", "additional card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266118, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["order new card", "replacement card", "additional card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I get additional cards?"

Keyphrases:
2404it [1:21:31,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzMW4a6poalFD4FvJ0GzJCsQa5t1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional cards", "extra card request", "issue more cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715266120, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["additional cards", "extra card request", "issue more cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a fee for extra cards?"

Keyphrases:
2405it [1:21:34,  1.97s/it]
ChatCompletion(id='chatcmpl-9MzMYVHFQGTj3Ws0gVtGEahh4ceRN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra card fee", "card charges", "additional card cost"]', role='assistant', function_call=None, tool_calls=None))], created=1715266122, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["extra card fee", "card charges", "additional card cost"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need some spare physical cards."

Keyphrases:
2406it [1:21:35,  1.87s/it]
ChatCompletion(id='chatcmpl-9MzMaAICXClznHwzhY6Igr58xG7C2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request additional cards", "physical card issuance", "extra bank cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715266124, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["request additional cards", "physical card issuance", "extra bank cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to receive a few more physical cards."

Keyphrases:
2407it [1:21:37,  1.78s/it]
ChatCompletion(id='chatcmpl-9MzMbnrp9WWLTXlhf9ztO1uNw9IO6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional cards", "request more cards", "physical card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715266125, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["additional cards", "request more cards", "physical card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I have a card after my first one?"

Keyphrases:
2408it [1:21:39,  1.99s/it]
ChatCompletion(id='chatcmpl-9MzMemuvgLPHidIDpDSJ3UkNfkhSc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card request", "extra card eligibility", "request second card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266128, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["additional card request", "extra card eligibility", "request second card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How would I go about getting a second card?"

Keyphrases:
2409it [1:21:42,  2.17s/it]
ChatCompletion(id='chatcmpl-9MzMflvSQ7xs5l4GWeip5TEpiHVmf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card", "request extra card", "second card application"]', role='assistant', function_call=None, tool_calls=None))], created=1715266129, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["additional card", "request extra card", "second card application"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'd like to have another card"

Keyphrases:
2410it [1:21:44,  2.23s/it]
ChatCompletion(id='chatcmpl-9MzMiZQrjqL3Haw0De7SDRNnucAdO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request additional card", "extra card", "additional bank card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266132, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["request additional card", "extra card", "additional bank card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I need more cards, are there any fees?"

Keyphrases:
2411it [1:21:45,  1.96s/it]
ChatCompletion(id='chatcmpl-9MzMkdMCuGXSOhNPRfvcSXAkx2MMn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional cards", "card fees", "extra card costs"]', role='assistant', function_call=None, tool_calls=None))], created=1715266134, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["additional cards", "card fees", "extra card costs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you offer multiple cards for the same account?"

Keyphrases:
2412it [1:21:47,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzMmQhmjmjUHdwbYwk9sTVIXhmuD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple cards", "additional cards", "same account cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715266136, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["multiple cards", "additional cards", "same account cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get a spare card for someone else to use?"

Keyphrases:
2413it [1:21:49,  1.80s/it]
ChatCompletion(id='chatcmpl-9MzMnrSsGSKG5XA7ez6C8ZfPPnqxy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card", "spare card", "card for another person"]', role='assistant', function_call=None, tool_calls=None))], created=1715266137, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["additional card", "spare card", "card for another person"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to get some more physical cards."

Keyphrases:
2414it [1:21:50,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzMpMXCYvvZzezDVLdmxOADlvPyD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["order more cards", "additional cards", "physical card request"]', role='assistant', function_call=None, tool_calls=None))], created=1715266139, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["order more cards", "additional cards", "physical card request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Would I be able to get another card for my account, so I could give one to my daughter?"

Keyphrases:
2415it [1:21:52,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzMq7reTM8LWYgDBFF1gYcZqGRbr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card", "secondary card request", "account card options"]', role='assistant', function_call=None, tool_calls=None))], created=1715266140, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=239, total_tokens=253))
["additional card", "secondary card request", "account card options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the procedure for getting another card?"

Keyphrases:
2416it [1:21:54,  1.70s/it]
ChatCompletion(id='chatcmpl-9MzMsC9sFtCng4XipJ31s3JZaUbyL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card replacement", "new card procedure", "issue new card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266142, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["card replacement", "new card procedure", "issue new card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I have a second card?"

Keyphrases:
2417it [1:21:57,  2.23s/it]
ChatCompletion(id='chatcmpl-9MzMun2qfI8jjw5bLLrfry9sS6ZDs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card", "request extra card", "second card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266144, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["additional card", "request extra card", "second card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My daughter would like a card as well, how can we make this happen?"

Keyphrases:
2418it [1:21:58,  1.99s/it]
ChatCompletion(id='chatcmpl-9MzMx4cPSPPCxH4z4FWqKvA2n5SMK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card", "family member card", "card request for relative"]', role='assistant', function_call=None, tool_calls=None))], created=1715266147, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["additional card", "family member card", "card request for relative"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I give a second card to my daughter?"

Keyphrases:
2419it [1:22:00,  1.91s/it]
ChatCompletion(id='chatcmpl-9MzMzQrcBvKo5pHwZPu5oUatq1xKX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card", "secondary card", "authorize card for family member"]', role='assistant', function_call=None, tool_calls=None))], created=1715266149, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["additional card", "secondary card", "authorize card for family member"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "May I have another card?"

Keyphrases:
2420it [1:22:02,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzN0lhnlbpMxumYp0dV6BXnfu0jC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request new card", "additional card", "issue new card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266150, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["request new card", "additional card", "issue new card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a fee for sending out more than one card?"

Keyphrases:
2421it [1:22:06,  2.47s/it]
ChatCompletion(id='chatcmpl-9MzN2bNt1cmX1cK0qUKNI1sFCFLQ6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card issuance fee", "multiple cards fee", "extra card charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715266152, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["card issuance fee", "multiple cards fee", "extra card charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I order extra cards?"

Keyphrases:
2422it [1:22:07,  2.10s/it]
ChatCompletion(id='chatcmpl-9MzN6DKwHTFWkhfDgIgwWFdL53QZ5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra cards", "order additional cards", "additional bank cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715266156, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["extra cards", "order additional cards", "additional bank cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I get a second card?"

Keyphrases:
2423it [1:22:08,  1.84s/it]
ChatCompletion(id='chatcmpl-9MzN7Hw6D3QXtuQYKqmC6HE2AUL4c', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card", "secondary card request", "issue extra card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266157, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["additional card", "secondary card request", "issue extra card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was looking to buy another card today."

Keyphrases:
2424it [1:22:10,  1.70s/it]
ChatCompletion(id='chatcmpl-9MzN8H4BumDAWlYidmuWXfdD2mEji', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["purchase card", "buy new card", "additional card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266158, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["purchase card", "buy new card", "additional card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need a few more physical cards."

Keyphrases:
2425it [1:22:11,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzNA4hsV3E7ZumuLNkdvfuehF2Hz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request additional cards", "physical card issuance", "extra bank cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715266160, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["request additional cards", "physical card issuance", "extra bank cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can i have a second physical card for this account?"

Keyphrases:
2426it [1:22:13,  1.80s/it]
ChatCompletion(id='chatcmpl-9MzNCycznZ4WoPcTVYaKzeLofdFSn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card request", "extra card", "second card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715266162, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["additional card request", "extra card", "second card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I purchase extra non-virtual cards?"

Keyphrases:
2427it [1:22:15,  1.78s/it]
ChatCompletion(id='chatcmpl-9MzNEIrh7ybIXPsaUx6v647FT8nM5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional cards", "order new card", "physical card purchase"]', role='assistant', function_call=None, tool_calls=None))], created=1715266164, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["additional cards", "order new card", "physical card purchase"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Am I allowed to give my daughter one of my cards to use?"

Keyphrases:
2428it [1:22:16,  1.61s/it]
ChatCompletion(id='chatcmpl-9MzNFbnrC9Gnlk9YvHhlSuzyuwjwj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card sharing", "authorized user", "additional cardholder"]', role='assistant', function_call=None, tool_calls=None))], created=1715266165, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["card sharing", "authorized user", "additional cardholder"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "May I have a second card?"

Keyphrases:
2429it [1:22:18,  1.65s/it]
ChatCompletion(id='chatcmpl-9MzNHR4IYWkMnHg0F9HAhjlr6W6dp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card", "request new card", "second card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715266167, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["additional card", "request new card", "second card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can i have a card to my daughter?"

Keyphrases:
2430it [1:22:19,  1.56s/it]
ChatCompletion(id='chatcmpl-9MzNIAMqPgshGe8M2dV8cbW3qGcPN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card", "card for family member", "dependent card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266168, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["additional card", "card for family member", "dependent card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there restrictions for ordering extra cards?"

Keyphrases:
2431it [1:22:21,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzNKuDnTKZEarpUjJV2sMZeub3z9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra cards", "card restrictions", "ordering limitations"]', role='assistant', function_call=None, tool_calls=None))], created=1715266170, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["extra cards", "card restrictions", "ordering limitations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I get a second card for my daughter?"

Keyphrases:
2432it [1:22:22,  1.51s/it]
ChatCompletion(id='chatcmpl-9MzNLeTw8AsGDUlAAdYgFSYmXwZgD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card", "family card", "secondary card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266171, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["additional card", "family card", "secondary card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I request another card?"

Keyphrases:
2433it [1:22:24,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzNNjNgA3uzO5WbvOJvQAjgVODyB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request new card", "replacement card", "issue new card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266173, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["request new card", "replacement card", "issue new card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Am I able to get a second card?"

Keyphrases:
2434it [1:22:26,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzNOcvHdeiWSNCrkeRbXiuBDLxsQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card", "second card request", "extra card eligibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715266174, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["additional card", "second card request", "extra card eligibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If you send me more cards, are there any charges?"

Keyphrases:
2435it [1:22:29,  1.99s/it]
ChatCompletion(id='chatcmpl-9MzNQrEO7SKCf5ks6iTXrO5k6CZ9l', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card fees", "extra card cost", "card issuance fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715266176, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["additional card fees", "extra card cost", "card issuance fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When trying to get more than one card is there a extra amount that needs to be paid?"

Keyphrases:
2436it [1:22:31,  2.00s/it]
ChatCompletion(id='chatcmpl-9MzNTVPPJhmiEgA9LnqEMNSinStUI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["multiple cards", "additional fees", "extra card costs"]', role='assistant', function_call=None, tool_calls=None))], created=1715266179, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=237, total_tokens=250))
["multiple cards", "additional fees", "extra card costs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to give a second card for this account to my daughter?"

Keyphrases:
2437it [1:22:33,  2.11s/it]
ChatCompletion(id='chatcmpl-9MzNVnsDqbqfVx6PWlkeUflhtpEj5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card", "secondary card account", "account authorization"]', role='assistant', function_call=None, tool_calls=None))], created=1715266181, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["additional card", "secondary card account", "account authorization"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My daughter needs a card. Can I give her one of mine that's linked to my account?"

Keyphrases:
2438it [1:22:34,  1.91s/it]
ChatCompletion(id='chatcmpl-9MzNXyzdTsX4AmcFfusPi6gSkpdnN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["additional card", "card sharing", "family banking"]', role='assistant', function_call=None, tool_calls=None))], created=1715266183, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=238, total_tokens=250))
["additional card", "card sharing", "family banking"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My child needs a card, how can I add them to the account I currently have?"

Keyphrases:
2439it [1:22:36,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzNZdngtuQOInvxSzxNqHQCOHiY4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["add child to account", "issue additional card", "child banking card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266185, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=236, total_tokens=252))
["add child to account", "issue additional card", "child banking card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "my daughter needs a card, how do i add her?"

Keyphrases:
2440it [1:22:38,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzNbRj6Ze8mFFuDJqUvfQ0mOkxah', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["add family member", "issue new card", "dependent card request"]', role='assistant', function_call=None, tool_calls=None))], created=1715266187, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["add family member", "issue new card", "dependent card request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I top up by cheque?"

Keyphrases:
2441it [1:22:41,  2.10s/it]
ChatCompletion(id='chatcmpl-9MzNceMOCHOqNcAT2sPv4JpzkBWiU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque top-up", "deposit by cheque", "account top-up methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715266188, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=225, total_tokens=242))
["cheque top-up", "deposit by cheque", "account top-up methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I top-up using cash?"

Keyphrases:
2442it [1:22:42,  1.92s/it]
ChatCompletion(id='chatcmpl-9MzNfiU73xSeY1JjzrnzCC2IMtCRl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash top-up", "manual reload", "using cash to top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266191, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["cash top-up", "manual reload", "using cash to top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I top up with a cheque?"

Keyphrases:
2443it [1:22:44,  1.97s/it]
ChatCompletion(id='chatcmpl-9MzNg41JZL5k87Bp6Uvb6SuL8zL75', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit", "top up account", "using cheque"]', role='assistant', function_call=None, tool_calls=None))], created=1715266192, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["cheque deposit", "top up account", "using cheque"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to top up with cash? If so how do I do it?"

Keyphrases:
2444it [1:22:46,  1.84s/it]
ChatCompletion(id='chatcmpl-9MzNiPA4OPWhongwt8ewzyKZC8cvI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash top-up", "reload account with cash", "how to add cash"]', role='assistant', function_call=None, tool_calls=None))], created=1715266194, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=235, total_tokens=252))
["cash top-up", "reload account with cash", "how to add cash"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you help me find top up by cash deposit?"

Keyphrases:
2445it [1:22:48,  1.90s/it]
ChatCompletion(id='chatcmpl-9MzNkjzEBkkhIbdNBEEvNHJQrWYpF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit", "top up options", "deposit methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715266196, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["cash deposit", "top up options", "deposit methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there an option to top up a with cheque?"

Keyphrases:
2446it [1:22:49,  1.82s/it]
ChatCompletion(id='chatcmpl-9MzNmUYbxSC7NGR3xT9mH3WMCoEvJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque top-up", "account funding with cheque", "depositing cheque"]', role='assistant', function_call=None, tool_calls=None))], created=1715266198, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["cheque top-up", "account funding with cheque", "depositing cheque"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Need to deposit a cheque into my account"

Keyphrases:
2447it [1:22:55,  2.90s/it]
ChatCompletion(id='chatcmpl-9MzNoQ7SewkHzvyb3GHFu1X6EeTdB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit", "bank account deposit", "depositing a cheque"]', role='assistant', function_call=None, tool_calls=None))], created=1715266200, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["cheque deposit", "bank account deposit", "depositing a cheque"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm looking for the cash deposit top up option but can't find it. Can you help me?"

Keyphrases:
2448it [1:22:56,  2.40s/it]
ChatCompletion(id='chatcmpl-9MzNtmp2qQLkmqrDtZyge4E3P19UC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit", "top up assistance", "deposit options"]', role='assistant', function_call=None, tool_calls=None))], created=1715266205, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=239, total_tokens=252))
["cash deposit", "top up assistance", "deposit options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I top up my account with a cash payment?"

Keyphrases:
2449it [1:22:58,  2.31s/it]
ChatCompletion(id='chatcmpl-9MzNuLuGXYUNEIQXwJZVDQ48OxsOY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit", "top up account", "account reloading"]', role='assistant', function_call=None, tool_calls=None))], created=1715266206, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["cash deposit", "top up account", "account reloading"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'd like to use cash to top up. How do I find that option?"

Keyphrases:
2450it [1:23:00,  2.06s/it]
ChatCompletion(id='chatcmpl-9MzNxvVGF2Ru0Rw1liQdArJgFZ21n', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash top-up", "cash deposit", "deposit options"]', role='assistant', function_call=None, tool_calls=None))], created=1715266209, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=235, total_tokens=248))
["cash top-up", "cash deposit", "deposit options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I locate topping up with cash."

Keyphrases:
2451it [1:23:01,  2.00s/it]
ChatCompletion(id='chatcmpl-9MzNyey2rznXeKn3buJk3MlEVR0ug', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash top-up location", "where to top up cash", "cash reloading points"]', role='assistant', function_call=None, tool_calls=None))], created=1715266210, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=227, total_tokens=245))
["cash top-up location", "where to top up cash", "cash reloading points"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I pay by check?"

Keyphrases:
2452it [1:23:03,  1.92s/it]
ChatCompletion(id='chatcmpl-9MzO0gLE5lconJtlQkT8wzg3IsNnq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["check payment", "pay with check", "using checks"]', role='assistant', function_call=None, tool_calls=None))], created=1715266212, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["check payment", "pay with check", "using checks"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I add to my account balance with a cheque?"

Keyphrases:
2453it [1:23:06,  2.20s/it]
ChatCompletion(id='chatcmpl-9MzO3wxjU3OMHzhtkFnFXNYJEOS4a', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit", "add balance", "account funding"]', role='assistant', function_call=None, tool_calls=None))], created=1715266215, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["cheque deposit", "add balance", "account funding"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What type of deposits do you accept into my account?"

Keyphrases:
2454it [1:23:09,  2.28s/it]
ChatCompletion(id='chatcmpl-9MzO41yXPWPFODcSSoQppnNSiVHhl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["deposit types", "acceptable deposits", "account funding options"]', role='assistant', function_call=None, tool_calls=None))], created=1715266216, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["deposit types", "acceptable deposits", "account funding options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I top up using a cheque?"

Keyphrases:
2455it [1:23:11,  2.30s/it]
ChatCompletion(id='chatcmpl-9MzO75ICTfIHHXCJ3fJHpsfiAggWC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit", "top up", "cheque top-up method"]', role='assistant', function_call=None, tool_calls=None))], created=1715266219, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["cheque deposit", "top up", "cheque top-up method"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you top-up a card with a cheque?"

Keyphrases:
2456it [1:23:13,  2.26s/it]
ChatCompletion(id='chatcmpl-9MzO9Zu0qATVa0hQSDaYQzb3DFxjP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque top-up", "card reload with cheque", "funding card with cheque"]', role='assistant', function_call=None, tool_calls=None))], created=1715266221, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=19, prompt_tokens=228, total_tokens=247))
["cheque top-up", "card reload with cheque", "funding card with cheque"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to top up cash, How do I do it?"

Keyphrases:
2457it [1:23:15,  2.11s/it]
ChatCompletion(id='chatcmpl-9MzOBavPf3gJxOMjhgj1WDCVIi8sC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash top up", "add money", "recharge account"]', role='assistant', function_call=None, tool_calls=None))], created=1715266223, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["cash top up", "add money", "recharge account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm looking for the option to top up by cheque."

Keyphrases:
2458it [1:23:16,  1.96s/it]
ChatCompletion(id='chatcmpl-9MzODVj5zXvvSxHqeFN5ilZUwFT4E', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque top-up", "deposit by cheque", "cheque deposit option"]', role='assistant', function_call=None, tool_calls=None))], created=1715266225, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["cheque top-up", "deposit by cheque", "cheque deposit option"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What locations can I top up with cash?"

Keyphrases:
2459it [1:23:19,  2.17s/it]
ChatCompletion(id='chatcmpl-9MzOFfck7cgEWHobuCU2dqrPpxDq7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash top up locations", "top up points", "reload with cash locations"]', role='assistant', function_call=None, tool_calls=None))], created=1715266227, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=17, prompt_tokens=227, total_tokens=244))
["cash top up locations", "top up points", "reload with cash locations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to top up using cash, where can I do that?"

Keyphrases:
2460it [1:23:21,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzOHtIl0zqp7qjG40KwmhCwDGAE9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash top up locations", "where to top up", "cash deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715266229, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["cash top up locations", "where to top up", "cash deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "is there a way to do top up with cash deposit"

Keyphrases:
2461it [1:23:22,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzOJgcq0uYDkmyGFCL0FNBc9C4k9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash top-up", "deposit cash", "cash deposit top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266231, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["cash top-up", "deposit cash", "cash deposit top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where are the options to top up with a cheque on my account?"

Keyphrases:
2462it [1:23:25,  2.21s/it]
ChatCompletion(id='chatcmpl-9MzOLvyTrlSsVEDJu2T229zwE28Tq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit", "account top-up options", "cheque top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266233, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=17, prompt_tokens=232, total_tokens=249))
["cheque deposit", "account top-up options", "cheque top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use cash to top up my account?"

Keyphrases:
2463it [1:23:27,  2.12s/it]
ChatCompletion(id='chatcmpl-9MzOOG5eJVgNwaYRDZE9vxlCk3Y03', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit", "account top-up", "using cash"]', role='assistant', function_call=None, tool_calls=None))], created=1715266236, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["cash deposit", "account top-up", "using cash"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I top up with cash?"

Keyphrases:
2464it [1:23:29,  1.97s/it]
ChatCompletion(id='chatcmpl-9MzOQjpz6orU6GJmtS8hwlmYYs786', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash top up", "deposit cash", "add money"]', role='assistant', function_call=None, tool_calls=None))], created=1715266238, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["cash top up", "deposit cash", "add money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will you accept a cheque to top up my account?"

Keyphrases:
2465it [1:23:31,  1.95s/it]
ChatCompletion(id='chatcmpl-9MzORmBDsItEEz4P5RE4JpinfhjHJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit", "account top-up", "cheque acceptance"]', role='assistant', function_call=None, tool_calls=None))], created=1715266239, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["cheque deposit", "account top-up", "cheque acceptance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I top up with this cheque I got?"

Keyphrases:
2466it [1:23:34,  2.29s/it]
ChatCompletion(id='chatcmpl-9MzOTD9vOtZPuZDvzdW4WRTsWStYq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit", "top up account", "using cheque"]', role='assistant', function_call=None, tool_calls=None))], created=1715266241, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["cheque deposit", "top up account", "using cheque"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What methods can I use to top up my account?"

Keyphrases:
2467it [1:23:37,  2.61s/it]
ChatCompletion(id='chatcmpl-9MzOWzasjsyEmE3eGlDR3Qghp4V1v', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up methods", "account recharge options", "funding methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715266244, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["top up methods", "account recharge options", "funding methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is cash good to top up with?"

Keyphrases:
2468it [1:23:39,  2.41s/it]
ChatCompletion(id='chatcmpl-9MzOa3MzW5gbvz2ROz3N0yqUsMYQw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up methods", "using cash for top up", "cash deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715266248, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["top up methods", "using cash for top up", "cash deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how come i can't find anywhere to load using cash"

Keyphrases:
2469it [1:23:41,  2.32s/it]
ChatCompletion(id='chatcmpl-9MzOb7Gx2QF5jNK0xHrqfArhAS4l9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash loading locations", "cash deposit", "load cash"]', role='assistant', function_call=None, tool_calls=None))], created=1715266249, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["cash loading locations", "cash deposit", "load cash"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What can I pay with? Does cash work?"

Keyphrases:
2470it [1:23:43,  2.16s/it]
ChatCompletion(id='chatcmpl-9MzOe20hMHbPh7A7DKYoPgIF1pKNJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment methods", "cash payment acceptance", "available payment options"]', role='assistant', function_call=None, tool_calls=None))], created=1715266252, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["payment methods", "cash payment acceptance", "available payment options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I deposit cash into my account?"

Keyphrases:
2471it [1:23:45,  2.13s/it]
ChatCompletion(id='chatcmpl-9MzOfNWVY4XAwVLNLilp0K1uf7W0p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash deposit", "deposit methods", "fund my account"]', role='assistant', function_call=None, tool_calls=None))], created=1715266253, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["cash deposit", "deposit methods", "fund my account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I top up with a cheque?"

Keyphrases:
2472it [1:23:46,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzOhTMZVG7xqcX36M0KWwMLZztpN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit", "top up issue", "cheque top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266255, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["cheque deposit", "top up issue", "cheque top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I send a cheque to do my top ups?"

Keyphrases:
2473it [1:23:48,  1.79s/it]
ChatCompletion(id='chatcmpl-9MzOjTQb80GFv8mCiZ5vN0RBkMA7C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque usage", "payment methods", "top-up by cheque"]', role='assistant', function_call=None, tool_calls=None))], created=1715266257, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["cheque usage", "payment methods", "top-up by cheque"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I top up my account with a cheque?"

Keyphrases:
2474it [1:23:56,  3.74s/it]
ChatCompletion(id='chatcmpl-9MzOkfMZrCuB1CkPg1iUsSyU4BWPV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit", "account top-up", "funding account with cheque"]', role='assistant', function_call=None, tool_calls=None))], created=1715266258, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["cheque deposit", "account top-up", "funding account with cheque"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to do a cash top-up"

Keyphrases:
2475it [1:23:58,  3.02s/it]
ChatCompletion(id='chatcmpl-9MzOtZRsB3MOSU2qdLKtbBRAIgg5Z', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash top-up", "add money", "fund account"]', role='assistant', function_call=None, tool_calls=None))], created=1715266267, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["cash top-up", "add money", "fund account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a cheque here, can I use it to top off my account?"

Keyphrases:
2476it [1:23:59,  2.60s/it]
ChatCompletion(id='chatcmpl-9MzOuMeIyX0vjWuI7LYj7maojC86X', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cheque deposit", "account top up", "using cheque"]', role='assistant', function_call=None, tool_calls=None))], created=1715266268, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["cheque deposit", "account top up", "using cheque"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to top-up using cash"

Keyphrases:
2477it [1:24:01,  2.25s/it]
ChatCompletion(id='chatcmpl-9MzOviEhQWsgjUDV4jyrUN0w8FKSF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash top-up", "manual reload", "add money"]', role='assistant', function_call=None, tool_calls=None))], created=1715266269, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["cash top-up", "manual reload", "add money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I top-up my card?"

Keyphrases:
2478it [1:24:02,  2.12s/it]
ChatCompletion(id='chatcmpl-9MzOxo3dAwvvZNutxyJpHxm67eW6V', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card top-up", "reload card", "add funds to card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266271, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["card top-up", "reload card", "add funds to card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I submit a check or cash payment?"

Keyphrases:
2479it [1:24:04,  1.89s/it]
ChatCompletion(id='chatcmpl-9MzOztj7F8UBA0QXxAGvLpjaTTlZS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment methods", "check payment", "cash payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715266273, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["payment methods", "check payment", "cash payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you accept checks?"

Keyphrases:
2480it [1:24:05,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzP0O8Zda1UdY5rHvMzwhxIRwokQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["accept checks", "payment methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715266274, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=8, prompt_tokens=223, total_tokens=231))
["accept checks", "payment methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I receive my physical card"

Keyphrases:
2481it [1:24:08,  2.16s/it]
ChatCompletion(id='chatcmpl-9MzP21cBTeDaV7j8GoXgklXWZ3b6m', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card delivery", "receive card", "card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715266276, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["physical card delivery", "receive card", "card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want a card. What is the procedure?"

Keyphrases:
2482it [1:24:10,  1.96s/it]
ChatCompletion(id='chatcmpl-9MzP5jxoR0eFVzatHiqRqLkwgb6qC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card application process", "how to get a card", "bank card procedure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266279, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["card application process", "how to get a card", "bank card procedure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do you charge for physical cards?"

Keyphrases:
2483it [1:24:11,  1.81s/it]
ChatCompletion(id='chatcmpl-9MzP6y9mEbrlsSdlHEI3BKIMQwRhy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fees", "physical card cost", "fee structure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266280, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card fees", "physical card cost", "fee structure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I get my card at?"

Keyphrases:
2484it [1:24:13,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzP8mA7oASHSRwGW4cEnwi5y0PMM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card pickup location", "where to get card", "card collection"]', role='assistant', function_call=None, tool_calls=None))], created=1715266282, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["card pickup location", "where to get card", "card collection"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "price of physical card"

Keyphrases:
2485it [1:24:14,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzP9arVKrAm0t2ePGst8MvUiN9ih', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card pricing", "cost of physical card", "physical card fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266283, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=223, total_tokens=238))
["card pricing", "cost of physical card", "physical card fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please, how do I order a card?"

Keyphrases:
2486it [1:24:16,  1.56s/it]
ChatCompletion(id='chatcmpl-9MzPBmspT6diOWE1Os1bcGJSAEtXO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["order new card", "request debit card", "card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715266285, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["order new card", "request debit card", "card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Send me a physical card"

Keyphrases:
2487it [1:24:17,  1.58s/it]
ChatCompletion(id='chatcmpl-9MzPC7eD7oY9Up81shq5eo1yezW6Y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request physical card", "physical card issuance", "card delivery request"]', role='assistant', function_call=None, tool_calls=None))], created=1715266286, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["request physical card", "physical card issuance", "card delivery request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to order a card. Where do you deliver to?"

Keyphrases:
2488it [1:24:19,  1.51s/it]
ChatCompletion(id='chatcmpl-9MzPDocHw3OcWHnVfvFJu0iKZgxoR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card order", "delivery locations", "shipping areas"]', role='assistant', function_call=None, tool_calls=None))], created=1715266287, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["card order", "delivery locations", "shipping areas"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I request a physical card?"

Keyphrases:
2489it [1:24:20,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzPFBzE4oN6uMqkIyc7tZKcHvnHv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card request", "card issuance", "request new card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266289, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["physical card request", "card issuance", "request new card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a charge for physical cards"

Keyphrases:
2490it [1:24:21,  1.39s/it]
ChatCompletion(id='chatcmpl-9MzPGWnimwdovBPCU9a8oq9gLGZUc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fees", "physical card charge", "card cost"]', role='assistant', function_call=None, tool_calls=None))], created=1715266290, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card fees", "physical card charge", "card cost"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you charge for physical cards"

Keyphrases:
2491it [1:24:25,  2.26s/it]
ChatCompletion(id='chatcmpl-9MzPIsnTGDcelbzH8KEhCOfT5r47R', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card fees", "card charges", "cost of physical card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266292, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["physical card fees", "card charges", "cost of physical card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you ship cards to where I live?"

Keyphrases:
2492it [1:24:28,  2.23s/it]
ChatCompletion(id='chatcmpl-9MzPMQJdpCrP8CuKeipUOcmmvKFFD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card shipping", "shipping availability", "card delivery location"]', role='assistant', function_call=None, tool_calls=None))], created=1715266296, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["card shipping", "shipping availability", "card delivery location"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "For physical cards, do you charge?"

Keyphrases:
2493it [1:24:29,  2.11s/it]
ChatCompletion(id='chatcmpl-9MzPOt0zOv0N1bODmoAYvTiuI980Y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card fees", "card charges", "cost of physical card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266298, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["physical card fees", "card charges", "cost of physical card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to get an actual card so that I can use it for in person transactions. How would I do this?"

Keyphrases:
2494it [1:24:31,  1.85s/it]
ChatCompletion(id='chatcmpl-9MzPQI4cFToiEit7budStV2US5GR7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card request", "obtain debit card", "card for transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715266300, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=242, total_tokens=258))
["physical card request", "obtain debit card", "card for transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will I get a real card?"

Keyphrases:
2495it [1:24:35,  2.61s/it]
ChatCompletion(id='chatcmpl-9MzPRCr7HoL1D7m1iIekwYPNasNry', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card", "card type", "real card availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715266301, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["physical card", "card type", "real card availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can you deliver cards?"

Keyphrases:
2496it [1:24:37,  2.32s/it]
ChatCompletion(id='chatcmpl-9MzPVWsbFyE69ffvXzl0hsetkQ5hA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery locations", "delivery areas", "card shipping destinations"]', role='assistant', function_call=None, tool_calls=None))], created=1715266305, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["card delivery locations", "delivery areas", "card shipping destinations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where are cards delivered to?"

Keyphrases:
2497it [1:24:38,  1.96s/it]
ChatCompletion(id='chatcmpl-9MzPXhy0DLJWnJ0Znh1hJfrwm53MU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery address", "delivery location", "shipping destination"]', role='assistant', function_call=None, tool_calls=None))], created=1715266307, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["card delivery address", "delivery location", "shipping destination"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please tell me how to get a physical card."

Keyphrases:
2498it [1:24:44,  3.25s/it]
ChatCompletion(id='chatcmpl-9MzPYLwbtJxgpm3b2SVzcSWG2wq43', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card request", "obtain debit card", "apply for physical card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266308, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["physical card request", "obtain debit card", "apply for physical card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the charge for a physical card?"

Keyphrases:
2499it [1:24:46,  2.95s/it]
ChatCompletion(id='chatcmpl-9MzPeifJfijRoA5b0GFaZKGuMemcp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card fee", "card charges", "cost of physical card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266314, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["physical card fee", "card charges", "cost of physical card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is a non-electronic card available as well"

Keyphrases:
2500it [1:24:48,  2.59s/it]
ChatCompletion(id='chatcmpl-9MzPhcmj1y5iRlAwpFrKGRQAhytXy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card type options", "non-electronic card availability", "alternative card options"]', role='assistant', function_call=None, tool_calls=None))], created=1715266317, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["card type options", "non-electronic card availability", "alternative card options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much does it cost in fees to use your card?"

Keyphrases:
2501it [1:24:49,  2.18s/it]
ChatCompletion(id='chatcmpl-9MzPiCg77tGGjT3DT49G35oHoQE7w', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card usage fees", "transaction fees", "fee structure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266318, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["card usage fees", "transaction fees", "fee structure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I get a physical card"

Keyphrases:
2502it [1:24:52,  2.20s/it]
ChatCompletion(id='chatcmpl-9MzPksLgdudAXNcMFnZF4eUG3fLUK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request physical card", "physical card issuance", "obtain debit card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266320, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["request physical card", "physical card issuance", "obtain debit card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get a physical card through this app?"

Keyphrases:
2503it [1:24:54,  2.22s/it]
ChatCompletion(id='chatcmpl-9MzPmPWghEVxqyTmwzTisGrt0Ji3x', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request physical card", "physical card availability", "bank card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715266322, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["request physical card", "physical card availability", "bank card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "can I have a non virtual card?"

Keyphrases:
2504it [1:24:55,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzPocs1O7XWVKbFf276sP2f9Nl2f', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card request", "non-virtual card", "card type change"]', role='assistant', function_call=None, tool_calls=None))], created=1715266324, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["physical card request", "non-virtual card", "card type change"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I get a physical card?"

Keyphrases:
2505it [1:24:57,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzPqGnbsu59YFonAUFBxhs9jkzEE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card request", "card issuance", "request debit card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266326, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["physical card request", "card issuance", "request debit card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the fees to get a physical card?"

Keyphrases:
2506it [1:24:59,  2.06s/it]
ChatCompletion(id='chatcmpl-9MzPr0PJCu9lMG7d81kw9QHbVZG1j', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fees", "physical card cost", "issuance fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266327, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["card fees", "physical card cost", "issuance fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can my card be delivered?"

Keyphrases:
2507it [1:25:01,  1.87s/it]
ChatCompletion(id='chatcmpl-9MzPuCt74BAMwxyTKKRcX1foyRswg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery locations", "delivery options", "delivery areas"]', role='assistant', function_call=None, tool_calls=None))], created=1715266330, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["card delivery locations", "delivery options", "delivery areas"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What will I be charged for a physical card?"

Keyphrases:
2508it [1:25:03,  1.89s/it]
ChatCompletion(id='chatcmpl-9MzPvPpij1I0XRqW1EPpbCtHq1ojL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card fee", "card charges", "cost of physical card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266331, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["physical card fee", "card charges", "cost of physical card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I order my card?"

Keyphrases:
2509it [1:25:04,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzPxUyYZnoSvwGaqxA4vG0wJ6UPQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["order new card", "card request", "apply for card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266333, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["order new card", "card request", "apply for card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What locations can a card be delivered to?"

Keyphrases:
2510it [1:25:06,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzPyhRiBCBQT4E5N5Vj3ybXL7aMN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery locations", "delivery areas", "card shipping destinations"]', role='assistant', function_call=None, tool_calls=None))], created=1715266334, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["card delivery locations", "delivery areas", "card shipping destinations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I receive my card?"

Keyphrases:
2511it [1:25:08,  1.81s/it]
ChatCompletion(id='chatcmpl-9MzQ1AeJz9JN35LBTAp7YmV1OkgpK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card receipt location", "card collection points", "where to get card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266337, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["card receipt location", "card collection points", "where to get card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do you deliver cards by mail?"

Keyphrases:
2512it [1:25:10,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzQ3ZEQWWZvcQyq1CWbVI7TPSEDI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery locations", "mail delivery areas", "card shipping zones"]', role='assistant', function_call=None, tool_calls=None))], created=1715266339, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["card delivery locations", "mail delivery areas", "card shipping zones"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I get a real-life card of my own?"

Keyphrases:
2513it [1:25:11,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzQ4JbojAOszQtc8J5036gQ079FB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card request", "bank card issuance", "apply for bank card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266340, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["physical card request", "bank card issuance", "apply for bank card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where will I find my card?"

Keyphrases:
2514it [1:25:14,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzQ6AYjqw8TaQkBr4cF6t4vOsO74', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card location", "find card", "card retrieval"]', role='assistant', function_call=None, tool_calls=None))], created=1715266342, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["card location", "find card", "card retrieval"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I want a physical card, do I have to pay anything?"

Keyphrases:
2515it [1:25:15,  1.78s/it]
ChatCompletion(id='chatcmpl-9MzQ8suNq26bqM6u55m8t2yP2phkT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card fees", "card issuance fee", "cost of physical card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266344, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["physical card fees", "card issuance fee", "cost of physical card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can cards be delivered?"

Keyphrases:
2516it [1:25:17,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzQ9ujX81WnILhp5PchjSYmNLzz0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card delivery locations", "delivery zones", "shipping areas"]', role='assistant', function_call=None, tool_calls=None))], created=1715266345, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["card delivery locations", "delivery zones", "shipping areas"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need a physical card."

Keyphrases:
2517it [1:25:19,  1.84s/it]
ChatCompletion(id='chatcmpl-9MzQBZf9oHYsIHe9U3G19nWh8dDx6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["request physical card", "physical card issuance", "debit card request"]', role='assistant', function_call=None, tool_calls=None))], created=1715266347, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["request physical card", "physical card issuance", "debit card request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the fees for a physical card?"

Keyphrases:
2518it [1:25:20,  1.71s/it]
ChatCompletion(id='chatcmpl-9MzQDE0gMwj0vhOMajZOoD2qZPxwu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card fees", "physical card costs", "banking fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266349, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["card fees", "physical card costs", "banking fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I get an actual card?"

Keyphrases:
2519it [1:25:22,  1.81s/it]
ChatCompletion(id='chatcmpl-9MzQFOwAWNzF8VEXeIGAdwPc1LF3Q', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card request", "request debit card", "issue new card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266351, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["physical card request", "request debit card", "issue new card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get a real card?"

Keyphrases:
2520it [1:25:25,  1.97s/it]
ChatCompletion(id='chatcmpl-9MzQHvgqMYaXDtZ1fd4cPy7nObkGa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["physical card request", "real card issuance", "debit card physical copy"]', role='assistant', function_call=None, tool_calls=None))], created=1715266353, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["physical card request", "real card issuance", "debit card physical copy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my disposable virtual card being denied?"

Keyphrases:
2521it [1:25:26,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzQJKZ7hIA0NrxhF3T8EWREIBXsf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issue", "card denial", "transaction denial"]', role='assistant', function_call=None, tool_calls=None))], created=1715266355, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["virtual card issue", "card denial", "transaction denial"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My disposable virtual card doesn't seem to work"

Keyphrases:
2522it [1:25:28,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzQKRrxxGMkYdt8sU9W9bszvAMkk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issue", "disposable card not working", "card functionality problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266356, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["virtual card issue", "disposable card not working", "card functionality problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My disposable virtual card is broken."

Keyphrases:
2523it [1:25:30,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzQMgZBYOsqzJM7VDfRNbTa6jEyC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issue", "broken card", "disposable card problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266358, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["virtual card issue", "broken card", "disposable card problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My non-physical card will not work"

Keyphrases:
2524it [1:25:32,  1.87s/it]
ChatCompletion(id='chatcmpl-9MzQOCKwEUjDEHIA4qiYXZT0hRxsq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["digital card issues", "non-physical card not working", "virtual card malfunction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266360, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=227, total_tokens=245))
["digital card issues", "non-physical card not working", "virtual card malfunction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did the disposable virtual card which I used to pay a gym subscription get denied?"

Keyphrases:
2525it [1:25:33,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzQQIUNzzZBDecA4pbgZXCC6EkmF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment denial", "virtual card issue", "gym payment problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266362, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=235, total_tokens=250))
["payment denial", "virtual card issue", "gym payment problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my virtual card is being declined?"

Keyphrases:
2526it [1:25:35,  1.80s/it]
ChatCompletion(id='chatcmpl-9MzQRdx5ds17NuwUw2gmFBa4BvfNS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "virtual card issue", "payment rejection"]', role='assistant', function_call=None, tool_calls=None))], created=1715266363, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["card declined", "virtual card issue", "payment rejection"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there restrictions for my disposable card since it does not seem to be working?"

Keyphrases:
2527it [1:25:36,  1.64s/it]
ChatCompletion(id='chatcmpl-9MzQTN9zSPHrAdAi1caGzqijVQslp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card issues", "card restrictions", "card not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715266365, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["disposable card issues", "card restrictions", "card not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I cannot get my virtual card to work."

Keyphrases:
2528it [1:25:38,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzQUwcwUUIXH4dPFLocKuuflyL9I', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "virtual card not working", "troubleshoot virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266366, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=227, total_tokens=245))
["virtual card issues", "virtual card not working", "troubleshoot virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was at the store earlier and my virtual card didn't work. What's the solution for this problem?"

Keyphrases:
2529it [1:25:40,  1.67s/it]
ChatCompletion(id='chatcmpl-9MzQW775AJM0Dc0eYn7FeuHM266G4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issue", "card not working", "payment solution"]', role='assistant', function_call=None, tool_calls=None))], created=1715266368, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=240, total_tokens=254))
["virtual card issue", "card not working", "payment solution"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My disposable virtual card will not work"

Keyphrases:
2530it [1:25:42,  1.90s/it]
ChatCompletion(id='chatcmpl-9MzQY8cvD4c2FhNcsYbEiK27yh0GG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issue", "disposable card not working", "card functionality problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266370, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["virtual card issue", "disposable card not working", "card functionality problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I cannot use my disposable virtual card."

Keyphrases:
2531it [1:25:44,  1.94s/it]
ChatCompletion(id='chatcmpl-9MzQaGnhraKBoOudETgjVlA242P9H', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issue", "disposable card not working", "virtual card error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266372, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["virtual card issue", "disposable card not working", "virtual card error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I make multiple online transactions with my virtual card?"

Keyphrases:
2532it [1:25:45,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzQcXVeYyJUuBoVdQYrI7xTVruV1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card transactions", "multiple transactions", "online transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715266374, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["virtual card transactions", "multiple transactions", "online transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was my virtual card declined when attempting to setup automatic billing?"

Keyphrases:
2533it [1:25:47,  1.64s/it]
ChatCompletion(id='chatcmpl-9MzQe47QX6y5sQ3TcZaUBr6dSO2FZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card declined", "automatic billing issue", "payment failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266376, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["virtual card declined", "automatic billing issue", "payment failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why doesn't my disposable virtual card work?"

Keyphrases:
2534it [1:25:49,  1.70s/it]
ChatCompletion(id='chatcmpl-9MzQfmVpwf0USpSzVNkCkMJjxOzis', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issue", "disposable card not working", "virtual card troubleshooting"]', role='assistant', function_call=None, tool_calls=None))], created=1715266377, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=227, total_tokens=244))
["virtual card issue", "disposable card not working", "virtual card troubleshooting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I use my virtual card for subscription services?"

Keyphrases:
2535it [1:25:50,  1.56s/it]
ChatCompletion(id='chatcmpl-9MzQhngLQE1hmQvoExV2F7NEFaeYY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "card restrictions", "subscription payment problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266379, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["virtual card issues", "card restrictions", "subscription payment problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why isn't my virtual card working?"

Keyphrases:
2536it [1:25:52,  1.71s/it]
ChatCompletion(id='chatcmpl-9MzQizETA0HuDaNUpmO0oH0tuY4oG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "virtual card not working", "troubleshoot virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266380, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=226, total_tokens=244))
["virtual card issues", "virtual card not working", "troubleshoot virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I cannot make transactions with my virtual card."

Keyphrases:
2537it [1:25:53,  1.58s/it]
ChatCompletion(id='chatcmpl-9MzQkKhLLxAzZA0Rg1U7YDsiRKARe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "transaction failure", "card functionality problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266382, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["virtual card issues", "transaction failure", "card functionality problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "For some reason, the virtual card won't work for me."

Keyphrases:
2538it [1:25:57,  2.14s/it]
ChatCompletion(id='chatcmpl-9MzQmaDKRn4UzIRVA1LnPDOnWwQD1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "virtual card not working", "troubleshooting virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266384, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=231, total_tokens=249))
["virtual card issues", "virtual card not working", "troubleshooting virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My disposable virtual card has been rejected by the merchant earlier today. What should I do?"

Keyphrases:
2539it [1:25:59,  2.11s/it]
ChatCompletion(id='chatcmpl-9MzQpKgnkDABcQZIRY7L2tEFgNENz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card rejection", "merchant rejection", "card troubleshooting"]', role='assistant', function_call=None, tool_calls=None))], created=1715266387, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=236, total_tokens=249))
["virtual card rejection", "merchant rejection", "card troubleshooting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I fix a problem where my virtual card is rejected?"

Keyphrases:
2540it [1:26:00,  2.00s/it]
ChatCompletion(id='chatcmpl-9MzQrOjwYQh2ipw6u06CMHSjrwoig', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "card rejection", "troubleshoot card rejection"]', role='assistant', function_call=None, tool_calls=None))], created=1715266389, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["virtual card issues", "card rejection", "troubleshoot card rejection"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My virtual card isn't working. What do I do?"

Keyphrases:
2541it [1:26:03,  2.14s/it]
ChatCompletion(id='chatcmpl-9MzQtLwyc8gLsgkq8DKG5wiKQ9TtG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "troubleshooting virtual card", "virtual card not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715266391, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=230, total_tokens=248))
["virtual card issues", "troubleshooting virtual card", "virtual card not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do if my virtual card won't work."

Keyphrases:
2542it [1:26:05,  1.97s/it]
ChatCompletion(id='chatcmpl-9MzQvTUVmlviuFa8mJGzqTed6VzQq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issue", "virtual card not working", "troubleshoot virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266393, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=230, total_tokens=248))
["virtual card issue", "virtual card not working", "troubleshoot virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a trick to get the disposable virtual card to work?"

Keyphrases:
2543it [1:26:06,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzQxZLxXUKGV9powS30yZpOKpeLY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "disposable card troubleshooting", "using virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266395, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=231, total_tokens=247))
["virtual card issues", "disposable card troubleshooting", "using virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I get my virtual card to work?"

Keyphrases:
2544it [1:26:07,  1.71s/it]
ChatCompletion(id='chatcmpl-9MzQyPRfzdmbLezyJBnVc3IhSp6Ey', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "virtual card not working", "troubleshoot virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266396, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=229, total_tokens=247))
["virtual card issues", "virtual card not working", "troubleshoot virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is just not working at this time."

Keyphrases:
2545it [1:26:09,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzR0gGjUxKpajv9cKk06OFgGvQVC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card malfunction", "card not working", "card issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715266398, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["card malfunction", "card not working", "card issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My disposable card seems not to be working am I doing something wrong?"

Keyphrases:
2546it [1:26:12,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzR2kGPjFutQhiPtDKKO8dAJ9jX2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card issues", "card not working", "troubleshoot card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266400, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=17, prompt_tokens=232, total_tokens=249))
["disposable card issues", "card not working", "troubleshoot card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My payments from my virtual card keep getting rejected."

Keyphrases:
2547it [1:26:14,  2.14s/it]
ChatCompletion(id='chatcmpl-9MzR4biCdSWBgdQAxJ7yYjyjWjPXT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "payment rejection", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266402, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["virtual card issues", "payment rejection", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My disposable virtual card is not working when I try to use it at a point of sale transaction. What do I do now?"

Keyphrases:
2548it [1:26:16,  2.02s/it]
ChatCompletion(id='chatcmpl-9MzR7zicuuPb6NpnSoSJgsqktLCo7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "point of sale problem", "card not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715266405, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=244, total_tokens=260))
["virtual card issues", "point of sale problem", "card not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transaction was just declined when I was using my disposable virtual card. What can I do?"

Keyphrases:
2549it [1:26:17,  1.82s/it]
ChatCompletion(id='chatcmpl-9MzR8FKL89hosnpFPe99QaWl76soZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transaction declined", "virtual card issue", "declined payment resolution"]', role='assistant', function_call=None, tool_calls=None))], created=1715266406, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=237, total_tokens=252))
["transaction declined", "virtual card issue", "declined payment resolution"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My disposable virtual card is not working"

Keyphrases:
2550it [1:26:19,  1.67s/it]
ChatCompletion(id='chatcmpl-9MzRAOYGuxb8SHipJtbRDQFEuwmGC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "disposable card not working", "card malfunction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266408, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["virtual card issues", "disposable card not working", "card malfunction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I get my disposable virtual card to work?"

Keyphrases:
2551it [1:26:20,  1.60s/it]
ChatCompletion(id='chatcmpl-9MzRBUcsVl7nnlqnEJT8dHUNQLFvd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issue", "activate virtual card", "disposable card not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715266409, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["virtual card issue", "activate virtual card", "disposable card not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How come my disposable virtual card used to pay for a gym subscription got rejected?"

Keyphrases:
2552it [1:26:22,  1.64s/it]
ChatCompletion(id='chatcmpl-9MzRDvgukYIfebUuArWyUnXieTIEd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["payment rejection", "virtual card issue", "subscription payment problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266411, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["payment rejection", "virtual card issue", "subscription payment problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Payments from my disposable virtual card don't work"

Keyphrases:
2553it [1:26:23,  1.61s/it]
ChatCompletion(id='chatcmpl-9MzRE0YTowB8niVaUsXlCubbDEk8N', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "payment failure", "disposable card not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715266412, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["virtual card issues", "payment failure", "disposable card not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My disposable virtual card was rejected by the merchant, please help?"

Keyphrases:
2554it [1:26:26,  1.99s/it]
ChatCompletion(id='chatcmpl-9MzRGjPrE1jmIpLOg8l6XjXy5jOe9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card rejection", "merchant card decline", "card not accepted"]', role='assistant', function_call=None, tool_calls=None))], created=1715266414, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["virtual card rejection", "merchant card decline", "card not accepted"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My virtual card won't work."

Keyphrases:
2555it [1:26:30,  2.59s/it]
ChatCompletion(id='chatcmpl-9MzRJtx23aqTlofElSGAr8D10ar60', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "virtual card not working", "card functionality problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266417, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["virtual card issues", "virtual card not working", "card functionality problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Tell me why my virtual disposable card won't work."

Keyphrases:
2556it [1:26:38,  4.21s/it]
ChatCompletion(id='chatcmpl-9MzRNww7RjZL9qHihYUSwnX8Sdcf7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "disposable card not working", "card functionality problems"]', role='assistant', function_call=None, tool_calls=None))], created=1715266421, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["virtual card issues", "disposable card not working", "card functionality problems"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need help getting the virtual card to work."

Keyphrases:
2557it [1:26:40,  3.47s/it]
ChatCompletion(id='chatcmpl-9MzRV7PUZmo9kS5Jbay7dvcXEOcPb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card assistance", "virtual card issues", "activate virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266429, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["virtual card assistance", "virtual card issues", "activate virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was trying to use my virtual card at a merchant and it was rejected. How can I fix this?"

Keyphrases:
2558it [1:26:43,  3.41s/it]
ChatCompletion(id='chatcmpl-9MzRWVxO97m6AbIJrKADcR6RGKVdJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card rejection", "merchant card rejection", "resolve card issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266430, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=240, total_tokens=255))
["virtual card rejection", "merchant card rejection", "resolve card issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I make my virtual card work?"

Keyphrases:
2559it [1:26:45,  2.96s/it]
ChatCompletion(id='chatcmpl-9MzRaMdb5YPrbU8pMRKDH78YeG58u', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card activation", "activate virtual card", "troubleshooting virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266434, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=227, total_tokens=244))
["virtual card activation", "activate virtual card", "troubleshooting virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "virtual card is not working for me"

Keyphrases:
2560it [1:26:47,  2.57s/it]
ChatCompletion(id='chatcmpl-9MzRbmLLm7hPFBl3Pk9Gnwyd2lfaK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issues", "card malfunction", "virtual card not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715266435, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["virtual card issues", "card malfunction", "virtual card not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I did not get the right amount of money when I used a different country's currency."

Keyphrases:
2561it [1:26:48,  2.14s/it]
ChatCompletion(id='chatcmpl-9MzRd7uoyltzsMWpdiAWBGiPSkYz2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency conversion issue", "incorrect transaction amount", "foreign currency transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266437, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["currency conversion issue", "incorrect transaction amount", "foreign currency transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I took out money from a transaction machine and it exchanged the wrong dollar value amount from another currency!"

Keyphrases:
2562it [1:26:50,  2.05s/it]
ChatCompletion(id='chatcmpl-9MzReZI2gFp6lJAkUow93MrEG4wnQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange error", "ATM withdrawal issue", "incorrect withdrawal amount"]', role='assistant', function_call=None, tool_calls=None))], created=1715266438, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=238, total_tokens=254))
["currency exchange error", "ATM withdrawal issue", "incorrect withdrawal amount"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a withdraw from the ATM this past holiday and it seems like a was charged too much. If I would have   known about these charges I wouldn't have made a withdraw."

Keyphrases:
2563it [1:27:03,  5.49s/it]
ChatCompletion(id='chatcmpl-9MzRgpjVAhDuFE28okHSFnGqNZK7q', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal charges", "excessive charges", "holiday banking fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266440, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=255, total_tokens=271))
["ATM withdrawal charges", "excessive charges", "holiday banking fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you look to make sure the exchange rate is correct"

Keyphrases:
2564it [1:27:05,  4.49s/it]
ChatCompletion(id='chatcmpl-9MzRuzF4O8Oy4AiyLo6UTq04ZPnvT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate verification", "correct exchange rate", "check exchange rate"]', role='assistant', function_call=None, tool_calls=None))], created=1715266454, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["exchange rate verification", "correct exchange rate", "check exchange rate"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Exchange rate for my cash withdrawal is wrong"

Keyphrases:
2565it [1:27:07,  3.60s/it]
ChatCompletion(id='chatcmpl-9MzRw8zMxDUpF8av3dcddyec07aRU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect exchange rate", "exchange rate issue", "cash withdrawal error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266456, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["incorrect exchange rate", "exchange rate issue", "cash withdrawal error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hello. I'm on holiday and didn't bring any cash with me. I need to withdrawal my home currency from one of your machines. Do you have any that will do this and is there a charge?"

Keyphrases:
2566it [1:27:12,  4.09s/it]
ChatCompletion(id='chatcmpl-9MzRx0DdVSI3pbCiLAoXZzdbQsYO9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency withdrawal", "ATM withdrawal", "withdrawal fees", "international ATM"]', role='assistant', function_call=None, tool_calls=None))], created=1715266457, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=18, prompt_tokens=260, total_tokens=278))
["currency withdrawal", "ATM withdrawal", "withdrawal fees", "international ATM"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was the exchange rate wrong when I got cash"

Keyphrases:
2567it [1:27:15,  3.54s/it]
ChatCompletion(id='chatcmpl-9MzS3EpzgN6vOesXYkgixdSu32NJM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate issue", "incorrect exchange rate", "currency conversion problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266463, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["exchange rate issue", "incorrect exchange rate", "currency conversion problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I attempted to get money using a foreign currency at an ATM but the rate was highly inaccurate!"

Keyphrases:
2568it [1:27:16,  2.94s/it]
ChatCompletion(id='chatcmpl-9MzS5NH23nvqDUrCFToRoSNXS667i', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign currency exchange", "ATM withdrawal issue", "currency rate problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266465, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=237, total_tokens=253))
["foreign currency exchange", "ATM withdrawal issue", "currency rate problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is the exchange rate wrong for my international withdrawal?"

Keyphrases:
2569it [1:27:18,  2.52s/it]
ChatCompletion(id='chatcmpl-9MzS6Bd30mH8qcvNP9nTfackMQflE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate issue", "incorrect exchange rate", "international withdrawal problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266466, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["exchange rate issue", "incorrect exchange rate", "international withdrawal problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "A wrong exchange rate was applied to a transaction made abroad."

Keyphrases:
2570it [1:27:20,  2.44s/it]
ChatCompletion(id='chatcmpl-9MzS88pnAEYnHnRgVB1WGBWgk0y0U', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect exchange rate", "foreign transaction error", "exchange rate issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266468, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["incorrect exchange rate", "foreign transaction error", "exchange rate issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The exchange rate you gave me for my cash withdrawal is wrong"

Keyphrases:
2571it [1:27:22,  2.29s/it]
ChatCompletion(id='chatcmpl-9MzSAO08MvTZxf6ilONO7agquSIeY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect exchange rate", "exchange rate dispute", "cash withdrawal issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266470, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["incorrect exchange rate", "exchange rate dispute", "cash withdrawal issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a fee for exchanging cash?"

Keyphrases:
2572it [1:27:24,  2.25s/it]
ChatCompletion(id='chatcmpl-9MzSCWX2WWaHjHnO5xObdTejA510w', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "exchange charges", "cash exchange fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715266472, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["currency exchange fee", "exchange charges", "cash exchange fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is the exchange rate so exorbitant? This should have been a much higher amount of cash for that to apply."

Keyphrases:
2573it [1:27:25,  1.96s/it]
ChatCompletion(id='chatcmpl-9MzSEl4VKy8N4gbmCOtZt6pqxKHCT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["high exchange rate", "exchange rate complaint", "currency conversion issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266474, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=243, total_tokens=258))
["high exchange rate", "exchange rate complaint", "currency conversion issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was the exchange rate different when I withdrew my cash?"

Keyphrases:
2574it [1:27:27,  1.81s/it]
ChatCompletion(id='chatcmpl-9MzSFaUEK8JIW2kEsiVhWP7VdD33h', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate issue", "currency conversion", "withdrawal rate discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715266475, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["exchange rate issue", "currency conversion", "withdrawal rate discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When I got cash, my exchange rate was wrong."

Keyphrases:
2575it [1:27:28,  1.62s/it]
ChatCompletion(id='chatcmpl-9MzSH22XkSTeauTJZoJiEW8xY9ANp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect exchange rate", "exchange rate issue", "currency conversion error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266477, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["incorrect exchange rate", "exchange rate issue", "currency conversion error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will there be additional costs of I make a withdrawal from a local ATM of British pounds? I need some cash to feel comfortable on the journey home"

Keyphrases:
2576it [1:27:29,  1.55s/it]
ChatCompletion(id='chatcmpl-9MzSIe44TpeKD3uwxBtDZSdcO2wyX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal fees", "withdrawal costs", "local ATM charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715266478, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=248, total_tokens=264))
["ATM withdrawal fees", "withdrawal costs", "local ATM charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It seems I was overcharged when I used an ATM while on vacation. If I knew about your fees in advance I sure would have gone somewhere else."

Keyphrases:
2577it [1:27:32,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzSK9wFqvd9NNdDMEtAJhiS334KO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["overcharged", "ATM fees", "transaction fees complaint"]', role='assistant', function_call=None, tool_calls=None))], created=1715266480, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=249, total_tokens=263))
["overcharged", "ATM fees", "transaction fees complaint"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I checked the exchange rate when I withdrew cash. But the actual rate that you applied was different."

Keyphrases:
2578it [1:27:34,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzSMZeRcOBKGIaa4tQu87BQwxw8L', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate issue", "incorrect exchange rate", "withdrawal rate discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715266482, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=238, total_tokens=254))
["exchange rate issue", "incorrect exchange rate", "withdrawal rate discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "In receiving cash, the wrong exchange rate was used for my transaction."

Keyphrases:
2579it [1:27:35,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzSOfZJP2hXBW4vSKMEMUVhvjsVc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect exchange rate", "transaction issue", "exchange rate error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266484, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["incorrect exchange rate", "transaction issue", "exchange rate error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I make a withdraw if I am out of country from with out any fees at an ATM?"

Keyphrases:
2580it [1:27:37,  1.70s/it]
ChatCompletion(id='chatcmpl-9MzSPaMvtb3hL8xN9ROq4Rr1sAkqL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international withdrawal", "ATM fees abroad", "no-fee withdrawal"]', role='assistant', function_call=None, tool_calls=None))], created=1715266485, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=238, total_tokens=254))
["international withdrawal", "ATM fees abroad", "no-fee withdrawal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I took out a foreign currency and the exchange rate is wrong."

Keyphrases:
2581it [1:27:38,  1.62s/it]
ChatCompletion(id='chatcmpl-9MzSRSzuOZy2IvcDRTrtGO8dHjnqP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign exchange issue", "incorrect exchange rate", "currency conversion error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266487, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["foreign exchange issue", "incorrect exchange rate", "currency conversion error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I feel like too much money was taken during my currency exchange."

Keyphrases:
2582it [1:27:40,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzSSY1VxXkVUIghwOeXZYINFkSRc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange issue", "exchange rate problem", "high exchange fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715266488, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["currency exchange issue", "exchange rate problem", "high exchange fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There was an error in exchange rate for my cash withdrawal"

Keyphrases:
2583it [1:27:42,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzSU5JiCK3eUcSUHM1f52wjeDwU0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate error", "cash withdrawal issue", "incorrect exchange rate"]', role='assistant', function_call=None, tool_calls=None))], created=1715266490, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["exchange rate error", "cash withdrawal issue", "incorrect exchange rate"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need the right foreign money, at the right rate, at ATMs, when I go abroad."

Keyphrases:
2584it [1:27:45,  2.11s/it]
ChatCompletion(id='chatcmpl-9MzSWtrm6UhKalmvOLmyyFI9zSQSH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign currency", "exchange rates", "ATM currency access"]', role='assistant', function_call=None, tool_calls=None))], created=1715266492, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=239, total_tokens=253))
["foreign currency", "exchange rates", "ATM currency access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The conversion rate on the ATM that I used with foreign currency was wrong."

Keyphrases:
2585it [1:27:47,  2.20s/it]
ChatCompletion(id='chatcmpl-9MzSZjvRFKVNaEwMfE8HbMfcU3nfh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect conversion rate", "ATM conversion issue", "foreign currency error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266495, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["incorrect conversion rate", "ATM conversion issue", "foreign currency error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "why is the exchange rate for a Foreign ATM different"

Keyphrases:
2586it [1:27:52,  2.98s/it]
ChatCompletion(id='chatcmpl-9MzSbgao2s1jADTNdw5gzdTGGPwHj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign ATM rates", "exchange rate discrepancy", "ATM exchange rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715266497, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["foreign ATM rates", "exchange rate discrepancy", "ATM exchange rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My cash withdrawal charged me the wrong exchange rate"

Keyphrases:
2587it [1:27:54,  2.66s/it]
ChatCompletion(id='chatcmpl-9MzSgFoYdwT5lhy2SqhPHlEl2ITou', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect exchange rate", "exchange rate issue", "cash withdrawal error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266502, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["incorrect exchange rate", "exchange rate issue", "cash withdrawal error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I withdrew some cash out of the ATM over the holiday. It seems that I was charged some outrageous fees. I would not have done that had I been aware of these outrageous charges!"

Keyphrases:
2588it [1:27:56,  2.55s/it]
ChatCompletion(id='chatcmpl-9MzSiRoa6bTP3E5EwGQ48eGja6h4z', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal fees", "unexpected charges", "holiday banking fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266504, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=255, total_tokens=270))
["ATM withdrawal fees", "unexpected charges", "holiday banking fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The exchange rate for my withdrawal isn't correct and doesn't match the actual exchange rate."

Keyphrases:
2589it [1:27:58,  2.30s/it]
ChatCompletion(id='chatcmpl-9MzSkVkVZVinDpTacbuUDMW0HFeqo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect exchange rate", "exchange rate discrepancy", "withdrawal exchange rate error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266506, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=236, total_tokens=253))
["incorrect exchange rate", "exchange rate discrepancy", "withdrawal exchange rate error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you explain your exchange rate policy? I don't think I received the correct amount of cash in my ATM transaction."

Keyphrases:
2590it [1:27:59,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzSmfkGO3vGQ7AXNEBb9aaDY0CIM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate policy", "incorrect cash amount", "ATM transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266508, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=242, total_tokens=258))
["exchange rate policy", "incorrect cash amount", "ATM transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My ecchange rate was wrong for a cash transaction."

Keyphrases:
2591it [1:28:02,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzSngQxQVNDrigZ5EnJybRq9uknh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate error", "incorrect exchange rate", "currency conversion issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266509, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["exchange rate error", "incorrect exchange rate", "currency conversion issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I expected a higher exchange rate when I withdrew money. Can you tell me current exchange rates?"

Keyphrases:
2592it [1:28:03,  2.02s/it]
ChatCompletion(id='chatcmpl-9MzSq525pf7uUbTtubsPIzF5SBag8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rates", "current exchange rates", "currency exchange information"]', role='assistant', function_call=None, tool_calls=None))], created=1715266512, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=237, total_tokens=251))
["exchange rates", "current exchange rates", "currency exchange information"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The see the rate applied to my transaction was wrong at the atm."

Keyphrases:
2593it [1:28:07,  2.39s/it]
ChatCompletion(id='chatcmpl-9MzSsxHkFf9C9jfE1eQnHHMqTucgj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect rate", "ATM transaction issue", "transaction rate error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266514, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["incorrect rate", "ATM transaction issue", "transaction rate error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The rate of exchange isn't right for my cash withdrawal."

Keyphrases:
2594it [1:28:08,  2.21s/it]
ChatCompletion(id='chatcmpl-9MzSvNDnwI50wuy6nxcILxMHF60Gi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate issue", "incorrect exchange rate", "cash withdrawal problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266517, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["exchange rate issue", "incorrect exchange rate", "cash withdrawal problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I took out cash abroad and the exchange rate isn't correct."

Keyphrases:
2595it [1:28:10,  1.92s/it]
ChatCompletion(id='chatcmpl-9MzSx7UWwu5pjTEgn6VmDXztBWBut', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect exchange rate", "foreign transaction issue", "exchange rate dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715266519, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["incorrect exchange rate", "foreign transaction issue", "exchange rate dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I used an ATM in a foreign currency but the rate applied is wrong!"

Keyphrases:
2596it [1:28:11,  1.82s/it]
ChatCompletion(id='chatcmpl-9MzSyp9jIMiewZionOba24dIV8i6F', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign currency transaction", "incorrect exchange rate", "ATM exchange issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266520, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["foreign currency transaction", "incorrect exchange rate", "ATM exchange issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how do you determine your exchange rates because one of yours was off when i got cash"

Keyphrases:
2597it [1:28:13,  1.65s/it]
ChatCompletion(id='chatcmpl-9MzT0fC9SZqAW8HI4VZeDODUxwT7p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rates", "currency conversion", "rate discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715266522, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=236, total_tokens=248))
["exchange rates", "currency conversion", "rate discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I used the ATM machine to get money out for Holiday shopping and saw the outrageous charges. Why is that? I would not have used the ATM if I had known!"

Keyphrases:
2598it [1:28:14,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzT1uxICWziP12AStazDPDDmaF87', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM charges", "withdrawal fees", "ATM fee complaint"]', role='assistant', function_call=None, tool_calls=None))], created=1715266523, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=252, total_tokens=268))
["ATM charges", "withdrawal fees", "ATM fee complaint"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The cash withdrawal exchange rate is not correct."

Keyphrases:
2599it [1:28:16,  1.61s/it]
ChatCompletion(id='chatcmpl-9MzT3LiOadoJIsTqIa6zYmYafMBwj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect exchange rate", "cash withdrawal issue", "exchange rate error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266525, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["incorrect exchange rate", "cash withdrawal issue", "exchange rate error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a local ATM that will provide British pounds, I have no money for my homeward journey and do not feel comfortable waiting until  I arrive in Britain. Will a withdrawal involve extra charges?"

Keyphrases:
2600it [1:28:18,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzT4YuTv2dysHdvVWs9h3RdOtSwH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign ATM", "currency exchange", "withdrawal charges", "local ATM with British pounds"]', role='assistant', function_call=None, tool_calls=None))], created=1715266526, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=20, prompt_tokens=258, total_tokens=278))
["foreign ATM", "currency exchange", "withdrawal charges", "local ATM with British pounds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "can i get a description of how to use a disposable virtual card"

Keyphrases:
2601it [1:28:19,  1.67s/it]
ChatCompletion(id='chatcmpl-9MzT6YN1CNQpZxm8l0lOjQfOqAn9D', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card usage", "using disposable card", "virtual card instructions"]', role='assistant', function_call=None, tool_calls=None))], created=1715266528, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["virtual card usage", "using disposable card", "virtual card instructions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I create a disposable virtual card?"

Keyphrases:
2602it [1:28:20,  1.51s/it]
ChatCompletion(id='chatcmpl-9MzT7mDLn8mZdvtuZcx8yZ4v5ncJz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card creation", "disposable card", "generate virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266529, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["virtual card creation", "disposable card", "generate virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What can you tell me about getting a virtual disposable card?"

Keyphrases:
2603it [1:28:22,  1.54s/it]
ChatCompletion(id='chatcmpl-9MzT92gYKSy4k98k2cC7eViv02oSH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "disposable card", "temporary banking card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266531, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["virtual card", "disposable card", "temporary banking card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to order a disposable virtual card. How can I do this?"

Keyphrases:
2604it [1:28:23,  1.48s/it]
ChatCompletion(id='chatcmpl-9MzTA1kYlEnb9dGYTCkR4FIKfZN7U', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card order", "disposable card", "order virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266532, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["virtual card order", "disposable card", "order virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how do VR cards work"

Keyphrases:
2605it [1:28:26,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzTChrSDOYw8lizYdPwvMaBLCanH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual reality cards", "VR card functionality", "how to use VR cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715266534, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=224, total_tokens=241))
["virtual reality cards", "VR card functionality", "how to use VR cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is a disposable virtual card?"

Keyphrases:
2606it [1:28:29,  2.14s/it]
ChatCompletion(id='chatcmpl-9MzTEiGLoU39zAVx7qW358iQalFDM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "disposable card", "temporary card usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715266536, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["virtual card", "disposable card", "temporary card usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like a temporary virtual card"

Keyphrases:
2607it [1:28:30,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzTHAzA4OF4ykR4s84K3EEhl0IkI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card request", "temporary card", "issue virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266539, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["virtual card request", "temporary card", "issue virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do the disposable cards work?"

Keyphrases:
2608it [1:28:31,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzTI1zirbxIpsu3c3jwlZOl1Qz1e', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable cards", "card functionality", "temporary card usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715266540, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["disposable cards", "card functionality", "temporary card usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I use a disposable virtual card?"

Keyphrases:
2609it [1:28:33,  1.82s/it]
ChatCompletion(id='chatcmpl-9MzTK618CgRTP6mQ4krlbaoXPaUQB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card usage", "disposable card guide", "how to use virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266542, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=227, total_tokens=245))
["virtual card usage", "disposable card guide", "how to use virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where's the best place to get a disposable virtual card?"

Keyphrases:
2610it [1:28:36,  1.89s/it]
ChatCompletion(id='chatcmpl-9MzTMvZ2fzFssB0nwr6VQFbNVS3a9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "disposable card", "best virtual card provider"]', role='assistant', function_call=None, tool_calls=None))], created=1715266544, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["virtual card", "disposable card", "best virtual card provider"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you explain the disposable cards to me?"

Keyphrases:
2611it [1:28:37,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzTOioptxfuR0YXh33hIKGhanPe4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable cards", "card features", "temporary card info"]', role='assistant', function_call=None, tool_calls=None))], created=1715266546, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["disposable cards", "card features", "temporary card info"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there anyway, I can get a disposable virtual card?"

Keyphrases:
2612it [1:28:40,  2.14s/it]
ChatCompletion(id='chatcmpl-9MzTQO4VER3ed6DnOGjn3aNoE1P67', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "disposable card", "temporary card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266548, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["virtual card", "disposable card", "temporary card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I just purchased a disposable virtual card. Am I able to use it for online purchases immediately?"

Keyphrases:
2613it [1:28:42,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzTSb2nzBN7Lzchupk8pwdrKzmsO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card usage", "immediate card activation", "disposable card online purchase"]', role='assistant', function_call=None, tool_calls=None))], created=1715266550, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=237, total_tokens=255))
["virtual card usage", "immediate card activation", "disposable card online purchase"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how secure is a disposable virtual card"

Keyphrases:
2614it [1:28:43,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzTU1CaqOlLoBS4RHSHF1SXhgV5D', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card security", "disposable card safety", "secure online payment"]', role='assistant', function_call=None, tool_calls=None))], created=1715266552, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["virtual card security", "disposable card safety", "secure online payment"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do to get a disposable virtual card?"

Keyphrases:
2615it [1:28:46,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzTVmvwFJt2C3cxooRBbSHHcs5nJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "disposable virtual card", "obtain virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266553, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["virtual card", "disposable virtual card", "obtain virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to get a disposable virtual card."

Keyphrases:
2616it [1:28:47,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzTYBbb7arYvn2Wi5FZ4zxVYsVgA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card request", "disposable card", "temporary card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266556, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["virtual card request", "disposable card", "temporary card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you explain disposable cards?"

Keyphrases:
2617it [1:28:49,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzTZW1bOeZH28DV1bmKOJkAQKHLK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable cards", "temporary card details", "one-time use card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266557, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=224, total_tokens=240))
["disposable cards", "temporary card details", "one-time use card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how do i get a virtual card for one time use"

Keyphrases:
2618it [1:28:50,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzTbSWiSUQxffYdAZSsdpZPpPP5g', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "one-time use card", "temporary card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266559, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["virtual card", "one-time use card", "temporary card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "May I get a disposable virtual card as well?"

Keyphrases:
2619it [1:28:52,  1.64s/it]
ChatCompletion(id='chatcmpl-9MzTcWkpJOYovzJ0fpaJcoJqZh4Fk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card request", "disposable card", "temporary card access"]', role='assistant', function_call=None, tool_calls=None))], created=1715266560, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["virtual card request", "disposable card", "temporary card access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can i get a single use virtual card"

Keyphrases:
2620it [1:28:53,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzTeQmLafEqWYFxvkVsiG8ZQ117f', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "single use card", "temporary card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266562, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["virtual card", "single use card", "temporary card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to create a disposable virtual card. How do I go about doing that?"

Keyphrases:
2621it [1:28:54,  1.45s/it]
ChatCompletion(id='chatcmpl-9MzTfnkH5V0Ir5FMMJGpOLjAgteWG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card creation", "disposable card setup", "generate virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266563, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=236, total_tokens=252))
["virtual card creation", "disposable card setup", "generate virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a disposable virtual card here, so would you tell me what to do with it?"

Keyphrases:
2622it [1:28:57,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzTgb3peRhui6HO6jwcUyDAXbRUI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card usage", "using disposable card", "guide virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266564, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=237, total_tokens=252))
["virtual card usage", "using disposable card", "guide virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how does a virtual card work"

Keyphrases:
2623it [1:28:58,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzTjRqDIiaJS0I5vZjiIRHDoHsb0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card usage", "virtual card functionality", "online card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266567, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["virtual card usage", "virtual card functionality", "online card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the process of obtaining a disposable virtual card"

Keyphrases:
2624it [1:29:01,  2.13s/it]
ChatCompletion(id='chatcmpl-9MzTkY49FVXMqSLMt8LOzxCgqKB6i', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issuance", "obtain disposable card", "virtual card process"]', role='assistant', function_call=None, tool_calls=None))], created=1715266568, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["virtual card issuance", "obtain disposable card", "virtual card process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What does a disposable virtual card do?"

Keyphrases:
2625it [1:29:03,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzTotrqrFevRaEextiaEeupKclEI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card usage", "disposable card features", "virtual card benefits"]', role='assistant', function_call=None, tool_calls=None))], created=1715266572, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["virtual card usage", "disposable card features", "virtual card benefits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When can I order a disposable virtual card?"

Keyphrases:
2626it [1:29:05,  1.96s/it]
ChatCompletion(id='chatcmpl-9MzTpbvV9IRA4CvE01TzsvbLPHIfU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card order", "disposable card timing", "order virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266573, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["virtual card order", "disposable card timing", "order virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to also get a disposable virtual card?"

Keyphrases:
2627it [1:29:07,  1.87s/it]
ChatCompletion(id='chatcmpl-9MzTrkfcPtTLsG0NGNO8wwovLqIev', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "disposable card", "virtual card availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715266575, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["virtual card", "disposable card", "virtual card availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I obtain a disposable virtual card?"

Keyphrases:
2628it [1:29:08,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzTttcgpqmVx444Ogly91zLbiObV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "temporary card", "disposable card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266577, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["virtual card", "temporary card", "disposable card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How would you use a disposable card?"

Keyphrases:
2629it [1:29:09,  1.61s/it]
ChatCompletion(id='chatcmpl-9MzTuQMOHBi89cCbP15urYaO701pL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card usage", "using disposable card", "temporary card instructions"]', role='assistant', function_call=None, tool_calls=None))], created=1715266578, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["disposable card usage", "using disposable card", "temporary card instructions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need a disposable virtual card, how do I get one?"

Keyphrases:
2630it [1:29:11,  1.71s/it]
ChatCompletion(id='chatcmpl-9MzTwRSDlagp2udB9Gg7BqD3fZjYZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "disposable card", "obtain virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266580, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["virtual card", "disposable card", "obtain virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do disposable cards work?"

Keyphrases:
2631it [1:29:15,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzTyEAWUvf6gr17EKz2l4r9pj77b', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable cards", "temporary card usage", "one-time use cards"]', role='assistant', function_call=None, tool_calls=None))], created=1715266582, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=224, total_tokens=240))
["disposable cards", "temporary card usage", "one-time use cards"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a disposable virtual card I can order?"

Keyphrases:
2632it [1:29:16,  1.84s/it]
ChatCompletion(id='chatcmpl-9MzU1fPzhuOXVYAF2Tzz4QUTMll9e', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "disposable card", "order virtual card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266585, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["virtual card", "disposable card", "order virtual card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I get a disposable virtual card?"

Keyphrases:
2633it [1:29:17,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzU2Vm9Jr3bLzfwg8My9Dexr7FXl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "disposable card", "temporary card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266586, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["virtual card", "disposable card", "temporary card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will I be able to get a disposable virtual card as well?"

Keyphrases:
2634it [1:29:18,  1.56s/it]
ChatCompletion(id='chatcmpl-9MzU3cnQMoup3aFDxIWkDdvasAju0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card", "disposable card", "temporary card access"]', role='assistant', function_call=None, tool_calls=None))], created=1715266587, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["virtual card", "disposable card", "temporary card access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hello! I need to order a disposable virtual card. Where can I do that at?"

Keyphrases:
2635it [1:29:20,  1.65s/it]
ChatCompletion(id='chatcmpl-9MzU46gncC9Kq9n9Ctxp5my5fzDWi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["order virtual card", "disposable card", "virtual card service"]', role='assistant', function_call=None, tool_calls=None))], created=1715266588, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["order virtual card", "disposable card", "virtual card service"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "where do I request a disposable virtual card?"

Keyphrases:
2636it [1:29:21,  1.52s/it]
ChatCompletion(id='chatcmpl-9MzU6cXy4j1Dpi7MgONOAmtyPsIUc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card request", "disposable card", "temporary card access"]', role='assistant', function_call=None, tool_calls=None))], created=1715266590, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["virtual card request", "disposable card", "temporary card access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can i get a throw away card"

Keyphrases:
2637it [1:29:23,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzU8WLwH4cN51qvJ7G0B1eRwIf3G', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["temporary card", "one-time use card", "disposable card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266592, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["temporary card", "one-time use card", "disposable card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how many transactions can i make with a disposable card"

Keyphrases:
2638it [1:29:24,  1.42s/it]
ChatCompletion(id='chatcmpl-9MzU9B4rCStIhJCWzkdd7n1LHQ1cc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable card limits", "transaction limits", "card usage restrictions"]', role='assistant', function_call=None, tool_calls=None))], created=1715266593, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["disposable card limits", "transaction limits", "card usage restrictions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are disposable cards?"

Keyphrases:
2639it [1:29:26,  1.48s/it]
ChatCompletion(id='chatcmpl-9MzUAUrDBbx7g4Euo0vDzFZXOm92G', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["disposable cards", "temporary cards", "card types"]', role='assistant', function_call=None, tool_calls=None))], created=1715266594, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["disposable cards", "temporary cards", "card types"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "what's the process for getting a disposable virtual card?"

Keyphrases:
2640it [1:29:27,  1.42s/it]
ChatCompletion(id='chatcmpl-9MzUCTEhkDtqSjdSjS3crmGjP6OA3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["virtual card issuance", "disposable card", "virtual card process"]', role='assistant', function_call=None, tool_calls=None))], created=1715266596, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["virtual card issuance", "disposable card", "virtual card process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app denied my topped up."

Keyphrases:
2641it [1:29:28,  1.40s/it]
ChatCompletion(id='chatcmpl-9MzUDKGyC4iDcX1kkKp4xUNxHHNOJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up failure", "app transaction denial", "failed top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266597, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["top-up failure", "app transaction denial", "failed top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Heyy I tried to top up with my card today but it failed! I just got the couple days before but it has worked last time. What's going on, can you double check please?"

Keyphrases:
2642it [1:29:29,  1.37s/it]
ChatCompletion(id='chatcmpl-9MzUEZfY5yUgoMuU3nxQR5cQyuDsC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up failed", "card issues", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266598, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=258, total_tokens=271))
["top up failed", "card issues", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a top up that didn't go through.  Why?"

Keyphrases:
2643it [1:29:31,  1.42s/it]
ChatCompletion(id='chatcmpl-9MzUGci7wHyk9hH6huGtAWV8D5cej', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "failed top up", "payment not processed"]', role='assistant', function_call=None, tool_calls=None))], created=1715266600, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["top up issue", "failed top up", "payment not processed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "So, I tried topping up my card for the today. Unfortunately, it failed. A couple of days back I used it and it works fine. Can you double check and tell me what's going on?"

Keyphrases:
2644it [1:29:33,  1.52s/it]
ChatCompletion(id='chatcmpl-9MzUHzLNJfLEoCSOxg0g5D4V6fGrP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up failed", "card top up issue", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266601, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=260, total_tokens=275))
["top up failed", "card top up issue", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did the app deny my top up?"

Keyphrases:
2645it [1:29:34,  1.43s/it]
ChatCompletion(id='chatcmpl-9MzUJxDeZGxGY4grZZ0dyzTAGJzAl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up denial", "app issue", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266603, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["top up denial", "app issue", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "please tell me why my top-up failed."

Keyphrases:
2646it [1:29:35,  1.35s/it]
ChatCompletion(id='chatcmpl-9MzUKvbAj5BYAhCMUfNyeKay46uqb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "failed top-up", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266604, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["top-up issue", "failed top-up", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top-up isn't working."

Keyphrases:
2647it [1:29:37,  1.36s/it]
ChatCompletion(id='chatcmpl-9MzULn5LOscSzOv8iCihArYIacxl3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issue", "failed top-up", "top-up not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715266605, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=225, total_tokens=241))
["top-up issue", "failed top-up", "top-up not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I attempted to top up but the app denied it."

Keyphrases:
2648it [1:29:38,  1.38s/it]
ChatCompletion(id='chatcmpl-9MzUNsuJE5Z6EG7E6ymwtBxtyaFfF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "app denial", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266607, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["top up issue", "app denial", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What reason did my top-up fail for?"

Keyphrases:
2649it [1:29:42,  2.11s/it]
ChatCompletion(id='chatcmpl-9MzUOmZtdQwcD74KZrHmhgQB66oUh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up failure", "reason for failure", "failed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266608, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["top-up failure", "reason for failure", "failed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why didn`t my topup go through?"

Keyphrases:
2650it [1:29:44,  2.03s/it]
ChatCompletion(id='chatcmpl-9MzUSWTw3KkGIt4c1zKyj2bAFR992', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["topup failure", "transaction not completed", "funds not added"]', role='assistant', function_call=None, tool_calls=None))], created=1715266612, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["topup failure", "transaction not completed", "funds not added"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I check to see if my top-up worked?"

Keyphrases:
2651it [1:29:48,  2.59s/it]
ChatCompletion(id='chatcmpl-9MzUUkg8VyBsTOW6rNEYZmbvK3B6u', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up status", "confirm top-up", "top-up success"]', role='assistant', function_call=None, tool_calls=None))], created=1715266614, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["top-up status", "confirm top-up", "top-up success"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top up didn't work."

Keyphrases:
2652it [1:29:49,  2.18s/it]
ChatCompletion(id='chatcmpl-9MzUYUz5dolJtTT7m5gNnK8X50G4k', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up failure", "payment not processed", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266618, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["top up failure", "payment not processed", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top up failed."

Keyphrases:
2653it [1:29:50,  1.89s/it]
ChatCompletion(id='chatcmpl-9MzUZ6TzD8I4nhB3orRg4Xvc7kuWu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "failed transaction", "payment failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266619, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["top up issue", "failed transaction", "payment failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why would my topup not go through?"

Keyphrases:
2654it [1:29:51,  1.79s/it]
ChatCompletion(id='chatcmpl-9MzUaWwqg2Mw7JP8ojEfZBuMIvYzY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["topup issue", "topup failure", "payment not processed"]', role='assistant', function_call=None, tool_calls=None))], created=1715266620, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["topup issue", "topup failure", "payment not processed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why caused my top up to not work?"

Keyphrases:
2655it [1:29:54,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzUcWi5dnXfsdALBDy6Lpkqm3KCe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "top up failure", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266622, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["top up issue", "top up failure", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did my top up not work?"

Keyphrases:
2656it [1:29:55,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzUezUL6j2S302YkTBYQMwNn5T3D', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up failure", "recharge issue", "failed top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266624, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["top up failure", "recharge issue", "failed top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was my top-up unsuccessful?"

Keyphrases:
2657it [1:29:57,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzUg6BSuTqTx7mTKKmwMlhTO5nDw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up failure", "failed top-up", "transaction unsuccessful"]', role='assistant', function_call=None, tool_calls=None))], created=1715266626, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["top-up failure", "failed top-up", "transaction unsuccessful"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My funding to my card didn't go through."

Keyphrases:
2658it [1:30:00,  2.11s/it]
ChatCompletion(id='chatcmpl-9MzUhF8MFjj124kL1ZTK7GbR06tf0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["funding issue", "card top-up failed", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266627, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["funding issue", "card top-up failed", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to know why my credit card was declined for top up? What is the deal here and why did it not go through?"

Keyphrases:
2659it [1:30:01,  1.91s/it]
ChatCompletion(id='chatcmpl-9MzUkRrLAjF9IhuEdn14Jop0fcCGG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["credit card declined", "payment failure", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266630, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=245, total_tokens=258))
["credit card declined", "payment failure", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I topped up but the app did not accept it."

Keyphrases:
2660it [1:30:03,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzUmxSQwFygYBAdtQBL2hdzP5ETw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up failure", "app transaction error", "balance not updated"]', role='assistant', function_call=None, tool_calls=None))], created=1715266632, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["top up failure", "app transaction error", "balance not updated"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app denied my top-up"

Keyphrases:
2661it [1:30:04,  1.55s/it]
ChatCompletion(id='chatcmpl-9MzUnfpYwM0zKMchrUWoG1JT9apwx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up denied", "app issue", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266633, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["top-up denied", "app issue", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think my top up did not work"

Keyphrases:
2662it [1:30:07,  2.12s/it]
ChatCompletion(id='chatcmpl-9MzUoMjzSQ9pYt2raD1m3tvaCadAt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up failure", "funds not credited", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266634, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["top up failure", "funds not credited", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top up was denied in the app."

Keyphrases:
2663it [1:30:08,  1.80s/it]
ChatCompletion(id='chatcmpl-9MzUr6lfl2Hc4NhiUE2wP8YTaBGNL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up denied", "payment failure", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266637, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["top up denied", "payment failure", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me if my pop-up went through?"

Keyphrases:
2664it [1:30:10,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzUtnLrbiMX802kqVz8zCHgZITRg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pop-up status", "transaction confirmation", "payment status"]', role='assistant', function_call=None, tool_calls=None))], created=1715266639, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["pop-up status", "transaction confirmation", "payment status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "can you check why I wasn't able to top up?"

Keyphrases:
2665it [1:30:11,  1.62s/it]
ChatCompletion(id='chatcmpl-9MzUu6TdfJLDDLPpl06RFY8lHIwYA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "funding failure", "unable to add funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715266640, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["top up issue", "funding failure", "unable to add funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How did my top-up fail?"

Keyphrases:
2666it [1:30:13,  1.60s/it]
ChatCompletion(id='chatcmpl-9MzUvOU9ITekVq9TeXVR4bJi0S8uR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issues", "failed top-up", "transaction failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266641, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["top-up issues", "failed top-up", "transaction failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top-up failed, WHY?"

Keyphrases:
2667it [1:30:14,  1.64s/it]
ChatCompletion(id='chatcmpl-9MzUxQ4f7l3Y7OnOMgomgA2AYqKX8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up failure", "failed transaction", "payment issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266643, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["top-up failure", "failed transaction", "payment issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried to top up. Why was it denied?"

Keyphrases:
2668it [1:30:16,  1.55s/it]
ChatCompletion(id='chatcmpl-9MzUzNj9p6pkHqdPMPdJPt7BvUIMB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up denied", "payment rejection", "funding issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266645, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["top up denied", "payment rejection", "funding issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What's the deal? My card was just denied for top up. Why is it not going through?"

Keyphrases:
2669it [1:30:17,  1.54s/it]
ChatCompletion(id='chatcmpl-9MzV0j23yePgMcCbc6epjSbGTp3Ta', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card denial", "top up issue", "transaction rejection"]', role='assistant', function_call=None, tool_calls=None))], created=1715266646, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=239, total_tokens=252))
["card denial", "top up issue", "transaction rejection"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't think my top up is working correctly"

Keyphrases:
2670it [1:30:19,  1.60s/it]
ChatCompletion(id='chatcmpl-9MzV25dYolLqdYsPz8tr9r9ucprh2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "top up not working", "funding problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266648, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["top up issue", "top up not working", "funding problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app won't let me top up my account"

Keyphrases:
2671it [1:30:21,  1.61s/it]
ChatCompletion(id='chatcmpl-9MzV3aCuO93RppwogFZsl0Vx5Mp0k', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "account reload problem", "app top up failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715266649, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["top up issue", "account reload problem", "app top up failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm not sure why my top up request was denied"

Keyphrases:
2672it [1:30:22,  1.65s/it]
ChatCompletion(id='chatcmpl-9MzV5B3hqNFGmA14MQJyJULGvpecJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up denied", "request rejection", "funding issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266651, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["top up denied", "request rejection", "funding issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I top up?"

Keyphrases:
2673it [1:30:24,  1.59s/it]
ChatCompletion(id='chatcmpl-9MzV7yJC4aJ8PW2l6iwCa8lwvZ4nL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issues", "funding account problem", "unable to add money"]', role='assistant', function_call=None, tool_calls=None))], created=1715266653, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=225, total_tokens=242))
["top up issues", "funding account problem", "unable to add money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top-up has failed."

Keyphrases:
2674it [1:30:25,  1.51s/it]
ChatCompletion(id='chatcmpl-9MzV8eLtlASeU6B9oxVBNtbe92jUU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up failure", "recharge unsuccessful", "failed payment top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266654, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=224, total_tokens=240))
["top-up failure", "recharge unsuccessful", "failed payment top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Problems with top up"

Keyphrases:
2675it [1:30:27,  1.52s/it]
ChatCompletion(id='chatcmpl-9MzV9ZoorzwUzLgS27dPodoKRgje7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up issues", "trouble topping up", "failed top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266655, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=224, total_tokens=240))
["top-up issues", "trouble topping up", "failed top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I really need money from my card today, but my card is getting declined. Please help!!"

Keyphrases:
2676it [1:30:28,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzVBsYIGI1JaNJlHaAaxGmRmmTLB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card declined", "urgent financial assistance", "access funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715266657, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=238, total_tokens=251))
["card declined", "urgent financial assistance", "access funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I know if my top up was unsuccessful?"

Keyphrases:
2677it [1:30:29,  1.45s/it]
ChatCompletion(id='chatcmpl-9MzVCs6u1M6Jry6w0KhTHrYqnKN3l', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up status", "failed top up", "transaction status"]', role='assistant', function_call=None, tool_calls=None))], created=1715266658, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["top up status", "failed top up", "transaction status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm pretty sure my top up failed. How do I fix this?"

Keyphrases:
2678it [1:30:31,  1.45s/it]
ChatCompletion(id='chatcmpl-9MzVEJ4vMnxJ6EdgmUOQiBR7iRVp4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up failure", "resolve top up issue", "failed transaction fix"]', role='assistant', function_call=None, tool_calls=None))], created=1715266660, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["top up failure", "resolve top up issue", "failed transaction fix"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "why isnt top up working"

Keyphrases:
2679it [1:30:33,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzVFF8WNYb7yHhmGhdRxubVaTo7h', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issues", "top up failure", "recharge problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266661, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["top up issues", "top up failure", "recharge problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me why my top up didn't work?"

Keyphrases:
2680it [1:30:35,  1.70s/it]
ChatCompletion(id='chatcmpl-9MzVH9WunjrRxigvVu2S7JMInhzAs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up failure", "failed transaction", "top up issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266663, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["top up failure", "failed transaction", "top up issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a transfer a few hours ago from a UK banking account.  I do not yet see the transfer.  Please check on this for me."

Keyphrases:
2681it [1:30:36,  1.56s/it]
ChatCompletion(id='chatcmpl-9MzVJZnURr9PZ2PLyGOKpqgYzuiDb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "transfer not showing"]', role='assistant', function_call=None, tool_calls=None))], created=1715266665, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=249, total_tokens=262))
["pending transfer", "transfer status", "transfer not showing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "the balance on my account didnt change when i transferred money"

Keyphrases:
2682it [1:30:37,  1.46s/it]
ChatCompletion(id='chatcmpl-9MzVKLqZwXfQvTmaLhq4hkKCeRHLG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer issue", "balance update", "money transfer problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715266666, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["transfer issue", "balance update", "money transfer problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long will it take for my transferred money to show up?"

Keyphrases:
2683it [1:30:39,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzVMMWPQwOJGIdkC6ZBwyf6Pc5MY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer duration", "money transfer time", "funds availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715266668, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["transfer duration", "money transfer time", "funds availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why didn't my balance change after I transferred some money?"

Keyphrases:
2684it [1:30:41,  1.57s/it]
ChatCompletion(id='chatcmpl-9MzVOPCelymrAbLZXGssMIClgUCnS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["balance update", "post-transfer balance", "transfer impact"]', role='assistant', function_call=None, tool_calls=None))], created=1715266670, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["balance update", "post-transfer balance", "transfer impact"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will my balance update after a transfer?"

Keyphrases:
2685it [1:30:42,  1.53s/it]
ChatCompletion(id='chatcmpl-9MzVPxaAAOBmt3pdADtzPwHqs696L', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["balance update", "post-transfer balance", "transfer processing time"]', role='assistant', function_call=None, tool_calls=None))], created=1715266671, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["balance update", "post-transfer balance", "transfer processing time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does it take for an international transfer into my account?"

Keyphrases:
2686it [1:30:44,  1.50s/it]
ChatCompletion(id='chatcmpl-9MzVRQqgk3YdvpkUM13Y4iSnAXWj9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international transfer time", "receive international transfer", "transfer duration"]', role='assistant', function_call=None, tool_calls=None))], created=1715266673, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["international transfer time", "receive international transfer", "transfer duration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The amount of time that transfers usually take from a UK account is what?I just completed a transfer and it is not showing up at all. I'm wondering at this point if everything is actually okay."

Keyphrases:
2687it [1:30:45,  1.48s/it]
ChatCompletion(id='chatcmpl-9MzVSrJ86SRak60PFQlBHVSgjH7ko', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer time", "UK account transfer delay", "transfer not showing", "transfer status"]', role='assistant', function_call=None, tool_calls=None))], created=1715266674, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=19, prompt_tokens=259, total_tokens=278))
["transfer time", "UK account transfer delay", "transfer not showing", "transfer status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will my transfer be available in my account."

Keyphrases:
2688it [1:30:46,  1.41s/it]
ChatCompletion(id='chatcmpl-9MzVT7h8fnkaaw8cmpymtMTtJvyJq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer status", "transfer processing time", "expected transfer date"]', role='assistant', function_call=None, tool_calls=None))], created=1715266675, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["transfer status", "transfer processing time", "expected transfer date"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I didn't get the money I transferred"

Keyphrases:
2689it [1:30:48,  1.51s/it]
ChatCompletion(id='chatcmpl-9MzVVtcvpDhaNehLXI4h71p3F7nzr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "transfer not received", "failed transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266677, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["missing transfer", "transfer not received", "failed transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I just completed a bank transfer and the balance didn't update"

Keyphrases:
2690it [1:30:51,  1.82s/it]
ChatCompletion(id='chatcmpl-9MzVW96y6GLqw8r7vyXi8Zu6KgPsT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bank transfer completion", "balance update", "transaction not reflecting"]', role='assistant', function_call=None, tool_calls=None))], created=1715266678, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["bank transfer completion", "balance update", "transaction not reflecting"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I transferred some money but I think it has gotten lost somewhere."

Keyphrases:
2691it [1:30:52,  1.67s/it]
ChatCompletion(id='chatcmpl-9MzVZvY4K2kSus0kLBjBvNkroOTTc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "transfer inquiry", "lost money transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266681, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["missing transfer", "transfer inquiry", "lost money transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long does a UK transfer take?"

Keyphrases:
2692it [1:30:54,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzVaOU2y7YrUrXhhKTug4hl2JYuW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["UK transfer time", "transfer duration", "transaction speed"]', role='assistant', function_call=None, tool_calls=None))], created=1715266682, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["UK transfer time", "transfer duration", "transaction speed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hello I made a bank transfer couple hours ago from my UK account but it doesn't show up yet. Can you please check if everything is alright with it?"

Keyphrases:
2693it [1:30:56,  1.80s/it]
ChatCompletion(id='chatcmpl-9MzVcTgwXTQGMxGDmYYJQNKjVJXRB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bank transfer status", "transfer not showing", "check transfer status"]', role='assistant', function_call=None, tool_calls=None))], created=1715266684, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=250, total_tokens=265))
["bank transfer status", "transfer not showing", "check transfer status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a transfer and am still waiting."

Keyphrases:
2694it [1:30:58,  1.82s/it]
ChatCompletion(id='chatcmpl-9MzVekUAVYgjAdkur9XVMuDSkiWrM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "waiting for transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266686, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["pending transfer", "transfer status", "waiting for transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made an out of country transfer and it hasn't went through yet."

Keyphrases:
2695it [1:30:59,  1.64s/it]
ChatCompletion(id='chatcmpl-9MzVgivcU6fDGk6ryD0Yv7gbIl6Kh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international transfer", "transfer delay", "out of country transfer status"]', role='assistant', function_call=None, tool_calls=None))], created=1715266688, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["international transfer", "transfer delay", "out of country transfer status"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "After the transfer, the balance did not update."

Keyphrases:
2696it [1:31:00,  1.48s/it]
ChatCompletion(id='chatcmpl-9MzVhDINoKrln866SfngVDVZBJhFT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["balance update", "transfer balance discrepancy", "balance not updated"]', role='assistant', function_call=None, tool_calls=None))], created=1715266689, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["balance update", "transfer balance discrepancy", "balance not updated"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Could you please check one of my transfer which i made few hours ago from my UK bank account, as its not showing yet."

Keyphrases:
2697it [1:31:01,  1.41s/it]
ChatCompletion(id='chatcmpl-9MzViIZaQvKSL0mUkU1l3FnoVwIqP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer status", "pending transfer", "transfer not showing"]', role='assistant', function_call=None, tool_calls=None))], created=1715266690, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=244, total_tokens=257))
["transfer status", "pending transfer", "transfer not showing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I had cash transferred but the balance did not change."

Keyphrases:
2698it [1:31:02,  1.35s/it]
ChatCompletion(id='chatcmpl-9MzVjjpCecBjMOiecY42mlKylSBvQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer balance issue", "unupdated balance", "cash transfer not reflected"]', role='assistant', function_call=None, tool_calls=None))], created=1715266691, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["transfer balance issue", "unupdated balance", "cash transfer not reflected"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't see my latest bank transfer"

Keyphrases:
2699it [1:31:04,  1.44s/it]
ChatCompletion(id='chatcmpl-9MzVl9w8kZQmkRyrttYWiYwsNswhA', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "transfer not showing", "bank transfer issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266693, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["missing transfer", "transfer not showing", "bank transfer issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My bank transfer is still not showing up in my account."

Keyphrases:
2700it [1:31:06,  1.54s/it]
ChatCompletion(id='chatcmpl-9MzVmBAsUKzuAjx00D2tox51HkuU1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing bank transfer", "transfer not credited", "delayed transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266694, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["missing bank transfer", "transfer not credited", "delayed transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a transfer and it doesnt' show up in my account."

Keyphrases:
2701it [1:31:08,  1.87s/it]
ChatCompletion(id='chatcmpl-9MzVpVhSh9ttMLL1F9G3ocuygVDIs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "transfer not showing", "transaction issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266697, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["missing transfer", "transfer not showing", "transaction issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I transferred some money but it is yet to arrive."

Keyphrases:
2702it [1:31:10,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzVrKjgh8qETwCr3UVZPNTfuyNcH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["money transfer status", "delayed transfer", "transfer not received"]', role='assistant', function_call=None, tool_calls=None))], created=1715266699, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["money transfer status", "delayed transfer", "transfer not received"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is my balance the same?  I processed a transfer."

Keyphrases:
2703it [1:31:12,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzVsCtlkXyrl1l00WANeoZarInxI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["balance inquiry", "transfer not reflected", "account balance unchanged"]', role='assistant', function_call=None, tool_calls=None))], created=1715266700, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["balance inquiry", "transfer not reflected", "account balance unchanged"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why don't I have my transfer?"

Keyphrases:
2704it [1:31:14,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzVu6V0nILckQw6iCtICFyNBxiEH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "transfer status", "delayed transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266702, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["missing transfer", "transfer status", "delayed transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why isn't the transfer on my account showing up?"

Keyphrases:
2705it [1:31:17,  2.09s/it]
ChatCompletion(id='chatcmpl-9MzVxmshbS1jlTn4kXJXa21Man9cK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "transfer not showing", "account update delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715266705, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["missing transfer", "transfer not showing", "account update delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The  money I transferred does not show in the balance."

Keyphrases:
2706it [1:31:18,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzVzzlmfKrHAJmWpIvDnYbko4Cyj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "balance update", "transfer not showing"]', role='assistant', function_call=None, tool_calls=None))], created=1715266707, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["missing transfer", "balance update", "transfer not showing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have completed a transfer but it is not showing up."

Keyphrases:
2707it [1:31:22,  2.35s/it]
ChatCompletion(id='chatcmpl-9MzW1zQdwRNgUOTvj8SIzW1jUyhoC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer not showing", "missing transfer", "completed transfer issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266709, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["transfer not showing", "missing transfer", "completed transfer issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I did a transfer to my account but it doesn't show up"

Keyphrases:
2708it [1:31:23,  2.12s/it]
ChatCompletion(id='chatcmpl-9MzW4KfAsfeRyQULKpTxslvsTH5OP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "transfer not showing", "account update delay"]', role='assistant', function_call=None, tool_calls=None))], created=1715266712, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["missing transfer", "transfer not showing", "account update delay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long until my transfer will be available to me"

Keyphrases:
2709it [1:31:24,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzW505nMNWxUY1PjqAyz1fDFgzo6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer availability", "transfer duration", "time until transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266713, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["transfer availability", "transfer duration", "time until transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why doesn't it show that I did a balance transfer?"

Keyphrases:
2710it [1:31:27,  2.09s/it]
ChatCompletion(id='chatcmpl-9MzW7hW43YAA8lS854QEVbFYXbqVR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["balance transfer issue", "balance not showing", "transfer discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715266715, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["balance transfer issue", "balance not showing", "transfer discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a bank transfer a couple of hours ago from my UK account.  It hasn't appeared, can you check to make sure it went through?"

Keyphrases:
2711it [1:31:29,  1.92s/it]
ChatCompletion(id='chatcmpl-9MzW9hozJpfJpw5MVsUEFa1iO0McK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bank transfer status", "transfer confirmation", "pending transfer check"]', role='assistant', function_call=None, tool_calls=None))], created=1715266717, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=249, total_tokens=263))
["bank transfer status", "transfer confirmation", "pending transfer check"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My transfer is pending."

Keyphrases:
2712it [1:31:31,  2.06s/it]
ChatCompletion(id='chatcmpl-9MzWBr181BsOLEPLzn5E3ImHYNGqC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["pending transfer", "transfer status", "delayed transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266719, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["pending transfer", "transfer status", "delayed transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hey, I try to make a bank transfer from my UK account a few hours ago, but it haven't show up yet. Please check my account to make sure everything alright with it?"

Keyphrases:
2713it [1:31:32,  1.89s/it]
ChatCompletion(id='chatcmpl-9MzWDelH8M4Kkn9JkvOagyNMlTH0x', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bank transfer delay", "transfer not showing", "account status check"]', role='assistant', function_call=None, tool_calls=None))], created=1715266721, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=256, total_tokens=271))
["bank transfer delay", "transfer not showing", "account status check"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is my transfer from [country]?"

Keyphrases:
2714it [1:31:34,  1.67s/it]
ChatCompletion(id='chatcmpl-9MzWF9Ton8tsgodzbwd6agOoULCJL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international transfer", "transfer status", "missing transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266723, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["international transfer", "transfer status", "missing transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I made a bank transfer and my account balance did not show it."

Keyphrases:
2715it [1:31:35,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzWG0gRX3NzEImtCLbh1YHcfbGlm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "balance update", "transfer not reflected"]', role='assistant', function_call=None, tool_calls=None))], created=1715266724, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["missing transfer", "balance update", "transfer not reflected"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where is my money? I transfered it and it isn't in my account."

Keyphrases:
2716it [1:31:37,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzWIAIIBpSmxvNBDVnQKj3bNNVfh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing transfer", "transfer not received", "money not in account"]', role='assistant', function_call=None, tool_calls=None))], created=1715266726, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=235, total_tokens=250))
["missing transfer", "transfer not received", "money not in account"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to know the time frame that is typical for a transfer from a UK account. I just made a transfer and it doesn't appear. I want to make sure everything is okay."

Keyphrases:
2717it [1:31:39,  1.70s/it]
ChatCompletion(id='chatcmpl-9MzWJs2TLb8Hs3LTmCEnT9rOGWOPd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["transfer time frame", "UK account transfer", "missing transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266727, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=256, total_tokens=270))
["transfer time frame", "UK account transfer", "missing transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why doesn't my balance reflect my transfer"

Keyphrases:
2718it [1:31:41,  1.97s/it]
ChatCompletion(id='chatcmpl-9MzWMgbXzZY9fmddk4ntHsxKUOjYZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["balance discrepancy", "transfer not reflected", "missing transfer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266730, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["balance discrepancy", "transfer not reflected", "missing transfer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My account balance has not gone up even though I just transferred money into it"

Keyphrases:
2719it [1:31:44,  2.11s/it]
ChatCompletion(id='chatcmpl-9MzWORPXe5EUGYVxRaEoXjvVXOLjE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["account balance", "transfer not reflected", "delay in balance update"]', role='assistant', function_call=None, tool_calls=None))], created=1715266732, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["account balance", "transfer not reflected", "delay in balance update"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will I see my new balance after making my bank transfer?"

Keyphrases:
2720it [1:31:45,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzWQn3omUPSyX0yrivOfkXbfm9Wm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["balance update", "post-transfer balance", "transfer impact on balance"]', role='assistant', function_call=None, tool_calls=None))], created=1715266734, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["balance update", "post-transfer balance", "transfer impact on balance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Think someone has took money out with my card. What shall I do?"

Keyphrases:
2721it [1:31:47,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzWSzqIuwD0SPEIRJDISMDnMoXN9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "fraudulent charge", "card security"]', role='assistant', function_call=None, tool_calls=None))], created=1715266736, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["unauthorized transaction", "fraudulent charge", "card security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a withdrawal that isn't mind in the app."

Keyphrases:
2722it [1:31:49,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzWTBSZad72Ewq56oPQd3Ht1Pdus', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "fraudulent transaction", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266737, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["unauthorized withdrawal", "fraudulent transaction", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I just lost my wallet and I see that they are already withdrawing money from my account. How can I stop this?"

Keyphrases:
2723it [1:31:51,  1.95s/it]
ChatCompletion(id='chatcmpl-9MzWVbYrW9M2vRI8cqiyhPCwDyZaM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stop unauthorized transactions", "report stolen card", "block card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266739, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=242, total_tokens=256))
["stop unauthorized transactions", "report stolen card", "block card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I didn't get cash from an ATM, but the app says I did"

Keyphrases:
2724it [1:31:53,  1.80s/it]
ChatCompletion(id='chatcmpl-9MzWXS8T5pf6HBiVTeDb10jfi0T8c', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM discrepancy", "cash withdrawal error", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266741, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["ATM discrepancy", "cash withdrawal error", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My app shows some cash I didn't get."

Keyphrases:
2725it [1:31:54,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzWZPm7iUepXq2dBQhGCSvOyUlaW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "app transaction error", "missing funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715266743, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["unrecognized transaction", "app transaction error", "missing funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is there a random withdrawal in my app?"

Keyphrases:
2726it [1:31:57,  2.07s/it]
ChatCompletion(id='chatcmpl-9MzWakUoszBlJ9rwjy0AR7Tq7Yahz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "suspicious transaction", "transaction query"]', role='assistant', function_call=None, tool_calls=None))], created=1715266744, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["unauthorized withdrawal", "suspicious transaction", "transaction query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a suspicious cash withdraw on the account."

Keyphrases:
2727it [1:32:00,  2.43s/it]
ChatCompletion(id='chatcmpl-9MzWddagsAhJUn3hf6fdDcdChHygt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["suspicious activity", "unauthorized withdrawal", "fraudulent transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266747, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["suspicious activity", "unauthorized withdrawal", "fraudulent transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I didn't get cash from an ATM, but according to the app a transaction was made when i didn't make it."

Keyphrases:
2728it [1:32:02,  2.13s/it]
ChatCompletion(id='chatcmpl-9MzWgRvBHeoW1BMEjGWbC0M2d7z61', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM transaction issue", "unauthorized transaction", "ATM cash not dispensed"]', role='assistant', function_call=None, tool_calls=None))], created=1715266750, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=19, prompt_tokens=243, total_tokens=262))
["ATM transaction issue", "unauthorized transaction", "ATM cash not dispensed"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app said I withdrew cash at an ATM and I didn't"

Keyphrases:
2729it [1:32:04,  2.07s/it]
ChatCompletion(id='chatcmpl-9MzWi1yBCGnLtuMllNTIDvTEqD3Yj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["false ATM withdrawal", "ATM transaction error", "unauthorized withdrawal"]', role='assistant', function_call=None, tool_calls=None))], created=1715266752, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["false ATM withdrawal", "ATM transaction error", "unauthorized withdrawal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My app says that I received cash from an ATM and I didn't."

Keyphrases:
2730it [1:32:06,  2.07s/it]
ChatCompletion(id='chatcmpl-9MzWkeHXTxICQo5KuzNbYqG7NSSxR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM transaction error", "unauthorized withdrawal", "false ATM alert"]', role='assistant', function_call=None, tool_calls=None))], created=1715266754, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["ATM transaction error", "unauthorized withdrawal", "false ATM alert"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I freeze my bank card, as there has been a strange withdrawal?"

Keyphrases:
2731it [1:32:07,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzWmz4VV0eFsPmtQpCNiTXUxtGdW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["freeze card", "unauthorized withdrawal", "card security"]', role='assistant', function_call=None, tool_calls=None))], created=1715266756, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=234, total_tokens=247))
["freeze card", "unauthorized withdrawal", "card security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I see a cash withdrawal that I did not perform."

Keyphrases:
2732it [1:32:09,  1.87s/it]
ChatCompletion(id='chatcmpl-9MzWnRW7chp6ILi9ZaRvmSuMArPXm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "fraudulent transaction", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266757, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["unauthorized withdrawal", "fraudulent transaction", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I checked the app and saw an extra cash withdrawal that I didn't authorize"

Keyphrases:
2733it [1:32:12,  2.34s/it]
ChatCompletion(id='chatcmpl-9MzWpws3hjQKcfztC46oiCkTlhr2L', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "fraudulent transaction", "security breach"]', role='assistant', function_call=None, tool_calls=None))], created=1715266759, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["unauthorized withdrawal", "fraudulent transaction", "security breach"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a strange cash withdrawal in my statement"

Keyphrases:
2734it [1:32:15,  2.33s/it]
ChatCompletion(id='chatcmpl-9MzWtlVQcFBan767eKRt22d1H9x6x', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "suspicious transaction", "fraudulent activity"]', role='assistant', function_call=None, tool_calls=None))], created=1715266763, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["unauthorized withdrawal", "suspicious transaction", "fraudulent activity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There's a cash withdraw on my statement that I didn't make."

Keyphrases:
2735it [1:32:17,  2.31s/it]
ChatCompletion(id='chatcmpl-9MzWvnEfsdTUxOiRUX1EmN6d8jc6M', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "fraudulent transaction", "dispute transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266765, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["unauthorized withdrawal", "fraudulent transaction", "dispute transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "i think someone is using my card to withdraw money. Someone stole my wallet. What can I do? it is urgent."

Keyphrases:
2736it [1:32:18,  2.07s/it]
ChatCompletion(id='chatcmpl-9MzWxN066eKSjwhHp1ngii6DLuVz8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen card", "unauthorized withdrawal", "emergency card block"]', role='assistant', function_call=None, tool_calls=None))], created=1715266767, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=243, total_tokens=258))
["stolen card", "unauthorized withdrawal", "emergency card block"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am seeing in the App a some cash withdrawal that its not mine"

Keyphrases:
2737it [1:32:24,  3.10s/it]
ChatCompletion(id='chatcmpl-9MzWzkHgpuoflJyFTJkBSK7XOnzP0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "fraudulent transaction", "cash withdrawal not recognized"]', role='assistant', function_call=None, tool_calls=None))], created=1715266769, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=233, total_tokens=250))
["unauthorized withdrawal", "fraudulent transaction", "cash withdrawal not recognized"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My account has a weird withdrawal."

Keyphrases:
2738it [1:32:26,  2.89s/it]
ChatCompletion(id='chatcmpl-9MzX4l50sz03r1fS754DvQT4pDSPE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "suspicious transaction", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715266774, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["unauthorized withdrawal", "suspicious transaction", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm unsure of a withdrawl in my statement."

Keyphrases:
2739it [1:32:28,  2.67s/it]
ChatCompletion(id='chatcmpl-9MzX7zFSd8xiYAIQg6QaRjIGect3a', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized withdrawal", "statement query", "suspicious transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266777, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["unrecognized withdrawal", "statement query", "suspicious transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It looks like someone else withdrew cash from my account, can you help?"

Keyphrases:
2740it [1:32:31,  2.56s/it]
ChatCompletion(id='chatcmpl-9MzX91S94dRmRcudbYI0CBVQtHlyr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "account security", "fraudulent transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266779, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["unauthorized withdrawal", "account security", "fraudulent transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I think I see a withdraw I did not make."

Keyphrases:
2741it [1:32:35,  3.05s/it]
ChatCompletion(id='chatcmpl-9MzXBSuHlKWi97nzvydH6vbJ9cPPs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "fraudulent transaction", "suspicious withdrawal"]', role='assistant', function_call=None, tool_calls=None))], created=1715266781, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["unauthorized withdrawal", "fraudulent transaction", "suspicious withdrawal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Some cash is showing up in my app that I did not get."

Keyphrases:
2742it [1:32:36,  2.55s/it]
ChatCompletion(id='chatcmpl-9MzXFBaJbLuhnjvRUarGnwCmQfVnn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "account discrepancy", "missing funds"]', role='assistant', function_call=None, tool_calls=None))], created=1715266785, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["unrecognized transaction", "account discrepancy", "missing funds"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is an unauthorized cash withdrawal from my account for 500£.  I definitely didn't make this withdrawal.  I need your help."

Keyphrases:
2743it [1:32:38,  2.40s/it]
ChatCompletion(id='chatcmpl-9MzXHqerZp18z3zULis2ol7jKv0tU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "fraudulent transaction", "security issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266787, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=247, total_tokens=262))
["unauthorized withdrawal", "fraudulent transaction", "security issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app is showing an ATM withdrawl that I didn't make."

Keyphrases:
2744it [1:32:40,  2.30s/it]
ChatCompletion(id='chatcmpl-9MzXJa9y9Ex1ew2mWKX5TsabrfWUG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized transaction", "ATM withdrawal dispute", "fraudulent transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266789, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=232, total_tokens=249))
["unauthorized transaction", "ATM withdrawal dispute", "fraudulent transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a odd withdrawal on my account."

Keyphrases:
2745it [1:32:42,  2.06s/it]
ChatCompletion(id='chatcmpl-9MzXLiFHY8JlRUoT7AAWNSCYcnwFi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "suspicious transaction", "account security issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715266791, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["unauthorized withdrawal", "suspicious transaction", "account security issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to cancel my card that got stolen a little while ago. Someone has already taken some money out and I don't want them to take anymore. Can you please do that?"

Keyphrases:
2746it [1:32:44,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzXNIvpl4nYhx7N11sG9B20hRhyZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel stolen card", "block card", "fraudulent transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715266793, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=255, total_tokens=270))
["cancel stolen card", "block card", "fraudulent transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I cancel my card? There are charges on my account that I didn't make."

Keyphrases:
2747it [1:32:46,  2.07s/it]
ChatCompletion(id='chatcmpl-9MzXOxsk4ZHsfrw5O2x5yEBMNzVZ6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cancel card", "fraudulent charges", "unauthorized transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715266794, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=15, prompt_tokens=237, total_tokens=252))
["cancel card", "fraudulent charges", "unauthorized transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is an error, the app says I made an ATM withdrawal and I didn't."

Keyphrases:
2748it [1:32:48,  2.00s/it]
ChatCompletion(id='chatcmpl-9MzXQcbxUMrVPYnp71HHdbbsAecVk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized ATM withdrawal", "ATM transaction error", "report ATM discrepancy"]', role='assistant', function_call=None, tool_calls=None))], created=1715266796, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=236, total_tokens=253))
["unauthorized ATM withdrawal", "ATM transaction error", "report ATM discrepancy"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can anyone help me, I lost my wallet and they've started withdrawing from my account."

Keyphrases:
2749it [1:32:49,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzXSJEYriOe3Jv6JPX4mSJEYgMFq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["lost wallet", "unauthorized transactions", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715266798, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=236, total_tokens=249))
["lost wallet", "unauthorized transactions", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do if I notice a strange withdrawl in my statement?"

Keyphrases:
2750it [1:32:51,  1.77s/it]
ChatCompletion(id='chatcmpl-9MzXUPbhZwU10TgpoMsN7LL1qYWI8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "fraudulent transaction", "reporting suspicious activity"]', role='assistant', function_call=None, tool_calls=None))], created=1715266800, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=233, total_tokens=250))
["unauthorized withdrawal", "fraudulent transaction", "reporting suspicious activity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't recognise a cash withdrawal"

Keyphrases:
2751it [1:32:57,  3.06s/it]
ChatCompletion(id='chatcmpl-9MzXVzGVhAesEhfNuqZY7975WJiWn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "dispute transaction", "fraudulent withdrawal"]', role='assistant', function_call=None, tool_calls=None))], created=1715266801, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["unrecognized transaction", "dispute transaction", "fraudulent withdrawal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Help!  My wallet was stolen and someone is taking money out.  I need this money!  What can I do?"

Keyphrases:
2752it [1:32:59,  2.80s/it]
ChatCompletion(id='chatcmpl-9MzXbLxZZEQBzVuK5Uu4VSwTmwZo5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["stolen wallet", "fraudulent transactions", "urgent account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715266807, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=244, total_tokens=260))
["stolen wallet", "fraudulent transactions", "urgent account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a cash withdrawal transaction that I am unsure of."

Keyphrases:
2753it [1:33:02,  2.66s/it]
ChatCompletion(id='chatcmpl-9MzXd9XfjutD2eujnfATBzTfuB1aG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "suspect transaction", "cash withdrawal query"]', role='assistant', function_call=None, tool_calls=None))], created=1715266809, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["unrecognized transaction", "suspect transaction", "cash withdrawal query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I didn't take out money from an ATM but my app statement shows that I did. How can I fix this?"

Keyphrases:
2754it [1:33:03,  2.33s/it]
ChatCompletion(id='chatcmpl-9MzXgAU0sK361o5BqLv8RkJZgAXsY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM dispute", "unauthorized withdrawal", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266812, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=242, total_tokens=256))
["ATM dispute", "unauthorized withdrawal", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Someone has stolen my card. Even though I have my card with me, someone just made a 500£ cash withdrawal. Please help as soon as possible."

Keyphrases:
2755it [1:33:05,  2.32s/it]
ChatCompletion(id='chatcmpl-9MzXhETihjxLj6kYJEMkblzvycuIT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card theft", "unauthorized withdrawal", "emergency assistance"]', role='assistant', function_call=None, tool_calls=None))], created=1715266813, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=250, total_tokens=263))
["card theft", "unauthorized withdrawal", "emergency assistance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Cash I didn't get shows in my app."

Keyphrases:
2756it [1:33:07,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzXk8qhC3hdP0Ry1nt0Vlc1qTBeR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["missing cash", "app discrepancy", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715266816, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["missing cash", "app discrepancy", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is a problem with my card. Somebody has removed money from my account in a town I haven't been to. Can you please freeze my account immediately?"

Keyphrases:
2757it [1:33:09,  2.03s/it]
ChatCompletion(id='chatcmpl-9MzXlwBFrldBm0uwEVLDGwiIXdoC8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["freeze account", "unauthorized transaction", "fraudulent charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715266817, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=250, total_tokens=265))
["freeze account", "unauthorized transaction", "fraudulent charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "There is an ATM withdrawl in the app I don't recognize."

Keyphrases:
2758it [1:33:10,  1.85s/it]
ChatCompletion(id='chatcmpl-9MzXndzHlBKSiPutAbJ94is2z8ar5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unrecognized transaction", "ATM withdrawal", "transaction dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715266819, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["unrecognized transaction", "ATM withdrawal", "transaction dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "A cash withdrawal is showing up that I didn't do."

Keyphrases:
2759it [1:33:12,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzXp2Ua4hMwfD3WewDeLHZF1leDj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unauthorized withdrawal", "dispute transaction", "fraudulent withdrawal"]', role='assistant', function_call=None, tool_calls=None))], created=1715266821, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["unauthorized withdrawal", "dispute transaction", "fraudulent withdrawal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The app made a mistake and said I made a cash withdrawal."

Keyphrases:
2760it [1:33:13,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzXqYWqpBt7BgIa2eDbJNDe4IWnn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["app error", "incorrect transaction", "cash withdrawal mistake"]', role='assistant', function_call=None, tool_calls=None))], created=1715266822, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["app error", "incorrect transaction", "cash withdrawal mistake"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there an exchange fee?"

Keyphrases:
2761it [1:33:14,  1.48s/it]
ChatCompletion(id='chatcmpl-9MzXsihIjp199WAHqoTwhJO14Dooc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange fee", "currency conversion", "transaction cost"]', role='assistant', function_call=None, tool_calls=None))], created=1715266824, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["exchange fee", "currency conversion", "transaction cost"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "whats your exchange rate"

Keyphrases:
2762it [1:33:16,  1.54s/it]
ChatCompletion(id='chatcmpl-9MzXtTxSpicaP6sZ7qbBThzHNYsLE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate", "currency conversion rate", "forex rate"]', role='assistant', function_call=None, tool_calls=None))], created=1715266825, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=224, total_tokens=238))
["exchange rate", "currency conversion rate", "forex rate"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are your currency exchange fees?"

Keyphrases:
2763it [1:33:18,  1.75s/it]
ChatCompletion(id='chatcmpl-9MzXueR6V149bu8D5nc3klxNOQ6te', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fees", "exchange rates", "transaction costs"]', role='assistant', function_call=None, tool_calls=None))], created=1715266826, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["currency exchange fees", "exchange rates", "transaction costs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I find the exchange rate?"

Keyphrases:
2764it [1:33:20,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzXw3u8yBRMuZnCP2xxdvrAgndAm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate", "currency conversion", "rate lookup"]', role='assistant', function_call=None, tool_calls=None))], created=1715266828, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["exchange rate", "currency conversion", "rate lookup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the base amount for cross-currency exchanges?"

Keyphrases:
2765it [1:33:21,  1.61s/it]
ChatCompletion(id='chatcmpl-9MzXyezt0J96Aw6QozcRMJ4skWp3Y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "base amount"]', role='assistant', function_call=None, tool_calls=None))], created=1715266830, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["currency exchange", "exchange rates", "base amount"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My work sends me all over the world, can I get a discount for all the money I have to exchange?"

Keyphrases:
2766it [1:33:23,  1.78s/it]
ChatCompletion(id='chatcmpl-9MzXz5w040A8hASM0Qs6l947Jhl6j', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange discount", "travel discount", "money exchange savings"]', role='assistant', function_call=None, tool_calls=None))], created=1715266831, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=241, total_tokens=255))
["currency exchange discount", "travel discount", "money exchange savings"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much more do I have to pay to exchange currencies?"

Keyphrases:
2767it [1:33:27,  2.25s/it]
ChatCompletion(id='chatcmpl-9MzY2Q1LKWHXcoASpJY5YnSih63q7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rate fee", "payment for currency exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715266834, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["currency exchange", "exchange rate fee", "payment for currency exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a fee for exchanging currencies?"

Keyphrases:
2768it [1:33:29,  2.37s/it]
ChatCompletion(id='chatcmpl-9MzY5y1Us9iq40nj5maQeYHgJqLjy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "transaction cost", "exchange rate fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715266837, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["currency exchange fee", "transaction cost", "exchange rate fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much does it cost to exchange currencies?"

Keyphrases:
2769it [1:33:31,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzY8P0bXwkGNZTWF1xDE6fPzytH3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "exchange cost", "transaction fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715266840, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["currency exchange fee", "exchange cost", "transaction fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "whats the exchange charge"

Keyphrases:
2770it [1:33:33,  2.00s/it]
ChatCompletion(id='chatcmpl-9MzYAqk6BONC2Nwnt01dygDK6cTIb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign exchange fees", "currency conversion charge", "exchange rate fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266842, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=224, total_tokens=239))
["foreign exchange fees", "currency conversion charge", "exchange rate fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there any discount for someone that exchanges currencies frequently?"

Keyphrases:
2771it [1:33:35,  1.98s/it]
ChatCompletion(id='chatcmpl-9MzYB6KP09nJiEVlJwcRdrfQTgB7P', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange discount", "frequent currency exchange", "exchange benefits"]', role='assistant', function_call=None, tool_calls=None))], created=1715266843, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["currency exchange discount", "frequent currency exchange", "exchange benefits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a fee to exchange foreign money?"

Keyphrases:
2772it [1:33:36,  1.82s/it]
ChatCompletion(id='chatcmpl-9MzYDSQ5qRSwFX0L9k81wnqq5sJpN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "foreign transaction charge", "exchange rate fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715266845, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["currency exchange fee", "foreign transaction charge", "exchange rate fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I have to pay for exchanging currencies?"

Keyphrases:
2773it [1:33:38,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzYECOyn7Qs1TrBuwcvR7nrlaJgs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "pay for currency exchange", "exchange rate fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715266846, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["currency exchange fee", "pay for currency exchange", "exchange rate fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Does it cost extra to exchange currencies?"

Keyphrases:
2774it [1:33:41,  2.26s/it]
ChatCompletion(id='chatcmpl-9MzYGptUtoLYdUTnlxORu8FlWQ1Wx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "exchange rate cost", "additional charges for currency exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715266848, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=226, total_tokens=243))
["currency exchange fee", "exchange rate cost", "additional charges for currency exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a fee for exchanging foreign currencies?"

Keyphrases:
2775it [1:33:44,  2.38s/it]
ChatCompletion(id='chatcmpl-9MzYJdexZt3ZqqLPYr1CVMvq8afYM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "foreign transaction cost", "exchange rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715266851, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["currency exchange fee", "foreign transaction cost", "exchange rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will I be charged a fee for exchanging foreign currencies?"

Keyphrases:
2776it [1:33:45,  2.16s/it]
ChatCompletion(id='chatcmpl-9MzYMRzZWUPq1ncZ1sXydhK6FqXjQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "foreign transaction charges", "exchange rate fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715266854, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["currency exchange fee", "foreign transaction charges", "exchange rate fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much is a cross currency exchange, and can I check to see if I have any discounts available?"

Keyphrases:
2777it [1:33:47,  1.98s/it]
ChatCompletion(id='chatcmpl-9MzYOr4b7r79JnCuMQD2yJCvfyVqf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange rates", "cross currency fees", "exchange discounts"]', role='assistant', function_call=None, tool_calls=None))], created=1715266856, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=239, total_tokens=253))
["currency exchange rates", "cross currency fees", "exchange discounts"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you offer a discount on multiple currency exchanges?"

Keyphrases:
2778it [1:33:50,  2.41s/it]
ChatCompletion(id='chatcmpl-9MzYP2G99rDaUpQcZNZO1C4JX237Q', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange discount", "multi-currency discount", "exchange rate offer"]', role='assistant', function_call=None, tool_calls=None))], created=1715266857, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["currency exchange discount", "multi-currency discount", "exchange rate offer"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much do I have to pay for the exchange fee?"

Keyphrases:
2779it [1:33:52,  2.13s/it]
ChatCompletion(id='chatcmpl-9MzYTfhNP6rEsB773n5EnJub9sWu4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange fee", "currency exchange cost", "fee amount"]', role='assistant', function_call=None, tool_calls=None))], created=1715266861, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["exchange fee", "currency exchange cost", "fee amount"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I want to exchange currency, will there be extras?"

Keyphrases:
2780it [1:33:53,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzYUfzxujsVlw4Ze3LQtAv5UrX03', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "additional fees", "exchange rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715266862, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["currency exchange", "additional fees", "exchange rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I need to exchange currency is there an extra fee?"

Keyphrases:
2781it [1:33:56,  2.05s/it]
ChatCompletion(id='chatcmpl-9MzYV5ERaieUOvvjUsPnGNdlzhTxl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "additional charges", "exchange rates"]', role='assistant', function_call=None, tool_calls=None))], created=1715266863, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["currency exchange fee", "additional charges", "exchange rates"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was wondering if there were any discounts offered for frequent currency exchanges?"

Keyphrases:
2782it [1:34:01,  3.08s/it]
ChatCompletion(id='chatcmpl-9MzYYFsskvF0ncJSeHer1ZXnB5UrS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange discounts", "frequent user benefits", "exchange rate offers"]', role='assistant', function_call=None, tool_calls=None))], created=1715266866, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["currency exchange discounts", "frequent user benefits", "exchange rate offers"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Would I be charged for exchanging currencies?"

Keyphrases:
2783it [1:34:05,  3.42s/it]
ChatCompletion(id='chatcmpl-9MzYdtPjW1IavhXfaFMp3MrYyExRh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "exchange charges", "foreign transaction fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715266871, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["currency exchange fee", "exchange charges", "foreign transaction fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the exchange fee?"

Keyphrases:
2784it [1:34:07,  2.85s/it]
ChatCompletion(id='chatcmpl-9MzYi7YCN7GYCsFmT8PYOsjOHgrlo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange fee", "currency conversion charge", "transaction costs"]', role='assistant', function_call=None, tool_calls=None))], created=1715266876, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["exchange fee", "currency conversion charge", "transaction costs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Does it cost to exchange currencies with this card?"

Keyphrases:
2785it [1:34:10,  2.86s/it]
ChatCompletion(id='chatcmpl-9MzYjcKAdYdE9lkYysxTqxQfZABys', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "exchange rate cost", "card foreign transaction fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715266877, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["currency exchange fee", "exchange rate cost", "card foreign transaction fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how much you charge for exhcange"

Keyphrases:
2786it [1:34:11,  2.37s/it]
ChatCompletion(id='chatcmpl-9MzYmFEImsoD8MDY1XvSZzjbKsqrI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange rate", "currency conversion fee", "transaction cost"]', role='assistant', function_call=None, tool_calls=None))], created=1715266880, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["exchange rate", "currency conversion fee", "transaction cost"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there any extra hidden fees for exchanging currencies?"

Keyphrases:
2787it [1:34:13,  2.18s/it]
ChatCompletion(id='chatcmpl-9MzYn4kmvjp4eg2mJODjfJ8GB9zsN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fees", "hidden fees", "additional charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715266881, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["currency exchange fees", "hidden fees", "additional charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When I travel, what will it cost to switch for my currency?"

Keyphrases:
2788it [1:34:15,  2.14s/it]
ChatCompletion(id='chatcmpl-9MzYpBQ9F6TbtQfphBv527NLnuun7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange rates", "travel costs", "foreign transaction fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266883, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["currency exchange rates", "travel costs", "foreign transaction fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much will I pay to exchange foreign currency?"

Keyphrases:
2789it [1:34:17,  2.05s/it]
ChatCompletion(id='chatcmpl-9MzYrARxiokefvRLMMvGZ81hFHRaJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "exchange rate cost", "foreign currency transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715266885, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["currency exchange fee", "exchange rate cost", "foreign currency transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Does it cost money for currency exchange services?"

Keyphrases:
2790it [1:34:19,  2.14s/it]
ChatCompletion(id='chatcmpl-9MzYtiYQh3dAzO7GSvgpz0bMp6q2p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fees", "cost of currency exchange", "exchange rate fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266887, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["currency exchange fees", "cost of currency exchange", "exchange rate fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there extra charges for exchanging currency?"

Keyphrases:
2791it [1:34:20,  1.96s/it]
ChatCompletion(id='chatcmpl-9MzYvMzVYHhIMcv0QjqYYwJsFtSJU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fees", "additional charges", "exchange rate fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266889, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["currency exchange fees", "additional charges", "exchange rate fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I will need to exchange currencies frequently, will I be able to get a discount?"

Keyphrases:
2792it [1:34:22,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzYxmczb6mxk5jUes92usE26t23o', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange discount", "frequent transactions"]', role='assistant', function_call=None, tool_calls=None))], created=1715266891, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=235, total_tokens=248))
["currency exchange", "exchange discount", "frequent transactions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a charge for a foreign currency exchange?"

Keyphrases:
2793it [1:34:24,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzYz6Rc1uRSfx5AW6tigoG93ztQ3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign exchange fee", "currency conversion charge", "international transaction cost"]', role='assistant', function_call=None, tool_calls=None))], created=1715266893, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["foreign exchange fee", "currency conversion charge", "international transaction cost"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a discount for frequently exchanging currencies?"

Keyphrases:
2794it [1:34:26,  1.87s/it]
ChatCompletion(id='chatcmpl-9MzZ1RsZoWAimAQ8gKNPiT88FOBpV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange discount", "frequent exchange benefits", "exchange rate offers"]', role='assistant', function_call=None, tool_calls=None))], created=1715266895, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["currency exchange discount", "frequent exchange benefits", "exchange rate offers"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the cost for an exchange fee?"

Keyphrases:
2795it [1:34:27,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzZ2ngSjWavQyb0i1jEJbeALkQEI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange fee cost", "currency exchange fee", "fee details"]', role='assistant', function_call=None, tool_calls=None))], created=1715266896, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["exchange fee cost", "currency exchange fee", "fee details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will it cost more money if my currency needs to be exchanged?"

Keyphrases:
2796it [1:34:32,  2.65s/it]
ChatCompletion(id='chatcmpl-9MzZ4RI4uWc78Fwin37dXEsXhBnrP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "exchange rates", "conversion fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266898, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=231, total_tokens=243))
["currency exchange", "exchange rates", "conversion fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to exchange currencies, but is there an extra charge to do so?"

Keyphrases:
2797it [1:34:35,  2.60s/it]
ChatCompletion(id='chatcmpl-9MzZ8Q7vSphqm90CwGdKEqHAA2zaJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "conversion charge", "additional costs for currency exchange"]', role='assistant', function_call=None, tool_calls=None))], created=1715266902, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=235, total_tokens=251))
["currency exchange fee", "conversion charge", "additional costs for currency exchange"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Does it cost anything for exchanges?"

Keyphrases:
2798it [1:34:37,  2.52s/it]
ChatCompletion(id='chatcmpl-9MzZBXuGpy5yRD389RAd7SLCHE8oS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["exchange fees", "cost of exchange", "transaction fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266905, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["exchange fees", "cost of exchange", "transaction fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I exchange money from abroad without additional costs?"

Keyphrases:
2799it [1:34:39,  2.39s/it]
ChatCompletion(id='chatcmpl-9MzZDjTevl7Ag4GvDRYMYg4DdL8nh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange", "no fee exchange", "international transaction costs"]', role='assistant', function_call=None, tool_calls=None))], created=1715266907, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["currency exchange", "no fee exchange", "international transaction costs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "does it cost to exchange currencies?"

Keyphrases:
2800it [1:34:40,  2.08s/it]
ChatCompletion(id='chatcmpl-9MzZFeYzm2u84Gb4XweKdjUsCDCDa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["currency exchange fee", "exchange rate cost", "conversion charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715266909, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["currency exchange fee", "exchange rate cost", "conversion charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a fee for using a European bank card to top up?"

Keyphrases:
2801it [1:34:43,  2.17s/it]
ChatCompletion(id='chatcmpl-9MzZHr1Zh4ZfGmFRj06VBSlwJqEPi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["European card fee", "bank card top up fee", "transaction cost"]', role='assistant', function_call=None, tool_calls=None))], created=1715266911, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["European card fee", "bank card top up fee", "transaction cost"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there any fees for adding money with an international card?"

Keyphrases:
2802it [1:34:46,  2.42s/it]
ChatCompletion(id='chatcmpl-9MzZJX7fg3uoG3KMtiBkuSm4thkM2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international transaction fees", "adding money fees", "international card usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715266913, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["international transaction fees", "adding money fees", "international card usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "i was charged when i used a us issued card. why and what cards are free to use to add money"

Keyphrases:
2803it [1:34:48,  2.40s/it]
ChatCompletion(id='chatcmpl-9MzZMTdmbbmk6mPbTrmM6LlCMRllT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign transaction fees", "US issued card charges", "fee-free cards", "adding money charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715266916, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=21, prompt_tokens=241, total_tokens=262))
["foreign transaction fees", "US issued card charges", "fee-free cards", "adding money charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Any hidden fees associated with the international card if money is added?"

Keyphrases:
2804it [1:34:49,  2.07s/it]
ChatCompletion(id='chatcmpl-9MzZOdeTwFjqjyeplE4rKJb3wZa2X', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["hidden fees", "international card fees", "fee inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715266918, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["hidden fees", "international card fees", "fee inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will I get charged for topping off my card?"

Keyphrases:
2805it [1:34:51,  1.94s/it]
ChatCompletion(id='chatcmpl-9MzZQieRTzlEjDVxvqLTV0FGeqiGN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up fee", "card recharge cost", "service charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715266920, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["top up fee", "card recharge cost", "service charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there charges for topping up US cards?"

Keyphrases:
2806it [1:34:53,  1.85s/it]
ChatCompletion(id='chatcmpl-9MzZRd4PbF8KVRWZAwN5Dyf1tIWbj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up fees", "US card charges", "card funding fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266921, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["top-up fees", "US card charges", "card funding fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there fees for top ups?"

Keyphrases:
2807it [1:34:54,  1.82s/it]
ChatCompletion(id='chatcmpl-9MzZTuVcPF8IkFOtNRkhmtIvxvv38', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up fees", "transaction charges", "service fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715266923, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["top up fees", "transaction charges", "service fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the charges for US cards with top up."

Keyphrases:
2808it [1:34:56,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzZVFxphuCIpJZgwmONOr4LFCY5k', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["US card charges", "top up fees", "card fee details"]', role='assistant', function_call=None, tool_calls=None))], created=1715266925, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["US card charges", "top up fees", "card fee details"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there an additional charge for topping up using a European card?"

Keyphrases:
2809it [1:34:58,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzZWlataDgs7SfRlbKQL8N3GTg9c', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up fees", "European card charges", "additional fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266926, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["top-up fees", "European card charges", "additional fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "In exchange for top ups will you take fees?"

Keyphrases:
2810it [1:35:00,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzZYDCUzLYTQDkKGXEm5tto60XXf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up fees", "exchange fees", "service charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715266928, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["top up fees", "exchange fees", "service charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I just topped off my card will I be charged for it?"

Keyphrases:
2811it [1:35:01,  1.67s/it]
ChatCompletion(id='chatcmpl-9MzZaRr5yCFDhXYZiQqA1Kr4nfpHf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card top-up", "fees for topping card", "card reload charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715266930, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["card top-up", "fees for topping card", "card reload charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much does it cost to top up by card?"

Keyphrases:
2812it [1:35:04,  1.94s/it]
ChatCompletion(id='chatcmpl-9MzZbZSR0ILjYAQEW8ypf5IvfBaHh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card top-up cost", "top-up fee", "transaction cost"]', role='assistant', function_call=None, tool_calls=None))], created=1715266931, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["card top-up cost", "top-up fee", "transaction cost"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there any fees if I use a European bank card for a top up?"

Keyphrases:
2813it [1:35:06,  2.04s/it]
ChatCompletion(id='chatcmpl-9MzZfCLiECwgjGdLsP4Va4Lv9SSRJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign transaction fees", "European bank card", "top up fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266935, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["foreign transaction fees", "European bank card", "top up fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the top-up fees?"

Keyphrases:
2814it [1:35:07,  1.91s/it]
ChatCompletion(id='chatcmpl-9MzZgsl65OKmPJRgcGs7Mf0FEjGD0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up fees", "banking fees", "service charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715266936, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=225, total_tokens=239))
["top-up fees", "banking fees", "service charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much is the charge to top up my card?"

Keyphrases:
2815it [1:35:10,  1.98s/it]
ChatCompletion(id='chatcmpl-9MzZiCi35TB9O0Cn9vpanDkL7EAU9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card top-up charge", "top-up fees", "card recharge cost"]', role='assistant', function_call=None, tool_calls=None))], created=1715266938, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["card top-up charge", "top-up fees", "card recharge cost"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much can I expect to pay to top up a US card?"

Keyphrases:
2816it [1:35:11,  1.91s/it]
ChatCompletion(id='chatcmpl-9MzZkIBFZNzoGq0bKAy4opGNTp75s', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up cost", "US card recharge", "top up fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715266940, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["top up cost", "US card recharge", "top up fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What fee is included if I top up by card?"

Keyphrases:
2817it [1:35:13,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzZm13zgFc1t7dSS0Oc8GBvkfF3Q', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up fee", "card top-up charges", "transaction costs"]', role='assistant', function_call=None, tool_calls=None))], created=1715266942, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["top-up fee", "card top-up charges", "transaction costs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I use a European bank card for top up, Do I get charged?"

Keyphrases:
2818it [1:35:16,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzZnkrKXCPTbPbsDJLTTghsSf4L7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign transaction fees", "European bank card usage", "top up charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715266943, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=234, total_tokens=250))
["foreign transaction fees", "European bank card usage", "top up charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will there be any extra fees for European bank card for top up?"

Keyphrases:
2819it [1:35:17,  1.95s/it]
ChatCompletion(id='chatcmpl-9MzZqFU6yIS8BzZ8uE6ougUxPaIqD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["European bank card fees", "top up fees", "extra charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715266946, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["European bank card fees", "top up fees", "extra charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will I be charged if I use European bank card for top up?"

Keyphrases:
2820it [1:35:19,  1.92s/it]
ChatCompletion(id='chatcmpl-9MzZsOyklMSfrcvVbEKpdoboTiKAX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["foreign transaction fees", "European card charges", "bank card top up fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266948, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=232, total_tokens=249))
["foreign transaction fees", "European card charges", "bank card top up fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I want to use a European bank card for a top up. Must I pay?"

Keyphrases:
2821it [1:35:21,  1.92s/it]
ChatCompletion(id='chatcmpl-9MzZu1n9gnRHHij5FjIucfxUAa8yt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["European bank card", "top up fees", "payment requirements"]', role='assistant', function_call=None, tool_calls=None))], created=1715266950, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["European bank card", "top up fees", "payment requirements"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will I be charged for topping up by card?"

Keyphrases:
2822it [1:35:23,  1.81s/it]
ChatCompletion(id='chatcmpl-9MzZvViXt4yc08GIpeDW9pR6E7Gnc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up fees", "card top-up charges", "fee query"]', role='assistant', function_call=None, tool_calls=None))], created=1715266951, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["top-up fees", "card top-up charges", "fee query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a fee for topping up"

Keyphrases:
2823it [1:35:25,  1.91s/it]
ChatCompletion(id='chatcmpl-9MzZxxhv0SxTiOab38CB0Gf9n9TnV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up fee", "account recharge cost", "service charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715266953, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["top-up fee", "account recharge cost", "service charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do you charge for top ups?"

Keyphrases:
2824it [1:35:26,  1.77s/it]
ChatCompletion(id='chatcmpl-9MzZzCMkF7PnglgQXQSifuOEJ23aa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up fees", "service charges", "transaction costs"]', role='assistant', function_call=None, tool_calls=None))], created=1715266955, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["top up fees", "service charges", "transaction costs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will it cost anything to top up a US card?"

Keyphrases:
2825it [1:35:28,  1.73s/it]
ChatCompletion(id='chatcmpl-9Mza0w5IZ2oXILg4zxGlA3wDM6b7S', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up fees", "US card charges", "no cost top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266956, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["top up fees", "US card charges", "no cost top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Does topping up my card have a fee?"

Keyphrases:
2826it [1:35:30,  1.73s/it]
ChatCompletion(id='chatcmpl-9Mza2s4tMfj8krOhhQhL7BEedVyJq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card top-up fee", "service charge", "additional fee for card top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266958, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=227, total_tokens=245))
["card top-up fee", "service charge", "additional fee for card top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there fees for adding money using an international card"

Keyphrases:
2827it [1:35:31,  1.61s/it]
ChatCompletion(id='chatcmpl-9Mza41bncKiK9rwGkT5OiQsbDY4eF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international fees", "adding money", "card fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266960, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["international fees", "adding money", "card fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When using a US card, what is the cost for a top up/off?"

Keyphrases:
2828it [1:35:33,  1.62s/it]
ChatCompletion(id='chatcmpl-9Mza5zbRoForPZqPSvN2NIatFlcKY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["US card fees", "top up cost", "card usage charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715266961, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=234, total_tokens=249))
["US card fees", "top up cost", "card usage charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to use a European card for a top up, what will the charge be?"

Keyphrases:
2829it [1:35:36,  2.14s/it]
ChatCompletion(id='chatcmpl-9Mza7f74HJvAhonlZef6liiKi1rR5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["European card usage", "top-up charges", "international card fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266963, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["European card usage", "top-up charges", "international card fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it okay to use a bank card to top up"

Keyphrases:
2830it [1:35:38,  2.04s/it]
ChatCompletion(id='chatcmpl-9MzaASsKFNA8X6aosPf7KhKe9VAwj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bank card usage", "top up with bank card", "card top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266966, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["bank card usage", "top up with bank card", "card top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Any fee for topping up?"

Keyphrases:
2831it [1:35:39,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzaCCFMqTqd2n4MicHDXapwwqR0t', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up fee", "additional charge", "service fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715266968, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["top up fee", "additional charge", "service fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there any fees for top ups?"

Keyphrases:
2832it [1:35:41,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzaD116lvXEDwyuJf77YrNM7se6p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up fees", "fee inquiry", "additional charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715266969, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["top up fees", "fee inquiry", "additional charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the fees of using an international card to add money?"

Keyphrases:
2833it [1:35:42,  1.60s/it]
ChatCompletion(id='chatcmpl-9MzaFItmIu67ierXA61RcC7uYbyIF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international fees", "card usage fees", "add money fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266971, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["international fees", "card usage fees", "add money fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a charge or discount if I use a European bank in a top up?"

Keyphrases:
2834it [1:35:44,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzaGyr2xFPYCTZNddF1xzJVHXRtz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bank charges", "discounts", "European bank usage", "top up fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266972, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=235, total_tokens=253))
["bank charges", "discounts", "European bank usage", "top up fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is their a fee for top ups?"

Keyphrases:
2835it [1:35:47,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzaJzUX2WRrEYiR1hhgyv5FMRo3n', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up fee", "charge for top up", "transaction cost"]', role='assistant', function_call=None, tool_calls=None))], created=1715266975, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["top up fee", "charge for top up", "transaction cost"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I top up using an international card"

Keyphrases:
2836it [1:35:49,  2.17s/it]
ChatCompletion(id='chatcmpl-9MzaLAIIj5OtRuAfp4Zzcpi7fWTAu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international top up", "using foreign card", "card acceptance for top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715266977, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=227, total_tokens=244))
["international top up", "using foreign card", "card acceptance for top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What will happen if I want to add money using an international card? Will I run into any fees?"

Keyphrases:
2837it [1:35:52,  2.20s/it]
ChatCompletion(id='chatcmpl-9MzaOxEeUF2BJMJLQ6QuiTFsILSW3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international card usage", "add money", "transaction fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266980, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=239, total_tokens=252))
["international card usage", "add money", "transaction fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there any extra fees for adding money into the international card?"

Keyphrases:
2838it [1:35:54,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzaQxUIQuPFwrOBYlaWpUHMbNh1F', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international card fees", "additional fees", "loading fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715266982, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["international card fees", "additional fees", "loading fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the fees for top ups?"

Keyphrases:
2839it [1:35:55,  1.94s/it]
ChatCompletion(id='chatcmpl-9MzaSXTVfGlKYgmI9uhGWVLZqnbia', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up fees", "banking charges", "transaction costs"]', role='assistant', function_call=None, tool_calls=None))], created=1715266984, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["top up fees", "banking charges", "transaction costs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the top up charges for US cards?"

Keyphrases:
2840it [1:35:57,  1.85s/it]
ChatCompletion(id='chatcmpl-9MzaT3CF4nWbqTFiKOmPFANHYp16s', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up charges", "US card fees", "card reload costs"]', role='assistant', function_call=None, tool_calls=None))], created=1715266985, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["top up charges", "US card fees", "card reload costs"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Could you please activate my card"

Keyphrases:
2841it [1:35:58,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzaVIyIjKhLRQIWce1WrjAuJRZYQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "enable card usage"]', role='assistant', function_call=None, tool_calls=None))], created=1715266987, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["card activation", "activate card", "enable card usage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to activate my card can you do that now?"

Keyphrases:
2842it [1:36:00,  1.75s/it]
ChatCompletion(id='chatcmpl-9MzaXPqljSQMXG2LFLAEyA1nSTCnw', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "immediate card activation"]', role='assistant', function_call=None, tool_calls=None))], created=1715266989, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["card activation", "activate card", "immediate card activation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I need to do to activate my new card?"

Keyphrases:
2843it [1:36:01,  1.62s/it]
ChatCompletion(id='chatcmpl-9MzaYpy6XXsfx8S9HOdEiSzWqVOKh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "new card setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715266990, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["card activation", "activate card", "new card setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Tell me how to go about activating my new card?"

Keyphrases:
2844it [1:36:03,  1.63s/it]
ChatCompletion(id='chatcmpl-9MzaaIMEr6UkXAO3vgzLt2U1UXka1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "new card setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715266992, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["card activation", "activate card", "new card setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I activate my card so I can start using it?"

Keyphrases:
2845it [1:36:04,  1.45s/it]
ChatCompletion(id='chatcmpl-9MzabuPdYc47YLcby7Bf9S69tVwRm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "begin using card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266993, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["card activation", "activate card", "begin using card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How long will it take to activate my new card?"

Keyphrases:
2846it [1:36:07,  1.84s/it]
ChatCompletion(id='chatcmpl-9MzacAz2chm8aqK7KVuKU25AqmQt3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation time", "activation delay", "new card activation"]', role='assistant', function_call=None, tool_calls=None))], created=1715266994, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["card activation time", "activation delay", "new card activation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What's the right way to activate my card?"

Keyphrases:
2847it [1:36:08,  1.75s/it]
ChatCompletion(id='chatcmpl-9Mzafp90WGJBe9JjuSVib2107nzm6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "how to activate card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266997, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["card activation", "activate card", "how to activate card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I received my new card, how is it activated?"

Keyphrases:
2848it [1:36:11,  2.02s/it]
ChatCompletion(id='chatcmpl-9Mzagey5uaSR3NzxX3urWnUpUv6cx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate new card", "how to activate card"]', role='assistant', function_call=None, tool_calls=None))], created=1715266998, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=229, total_tokens=244))
["card activation", "activate new card", "how to activate card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a way my new card can be renewed?"

Keyphrases:
2849it [1:36:12,  1.85s/it]
ChatCompletion(id='chatcmpl-9Mzaj6jxgAXJLeEqgMnCpjXaZXlu8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["renew card", "card renewal", "new card renewal"]', role='assistant', function_call=None, tool_calls=None))], created=1715267001, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["renew card", "card renewal", "new card renewal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I activate a card I received?"

Keyphrases:
2850it [1:36:13,  1.63s/it]
ChatCompletion(id='chatcmpl-9MzaltMiizR1DuF9TUER85JLQqSy6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "card setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715267003, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["card activation", "activate card", "card setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I activate my card?"

Keyphrases:
2851it [1:36:15,  1.57s/it]
ChatCompletion(id='chatcmpl-9Mzam8YyOdOmmzjXODrsBmOaSmuDE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activation issue", "unable to activate card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267004, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["card activation", "activation issue", "unable to activate card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the process of card activation?"

Keyphrases:
2852it [1:36:17,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzanFt0HvRUNvVbEwWpZNUnpGUhP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation process", "activate card", "how to activate card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267005, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["card activation process", "activate card", "how to activate card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "WHAT CAN I DO AFTER THE CARD MISSING"

Keyphrases:
2853it [1:36:18,  1.61s/it]
ChatCompletion(id='chatcmpl-9Mzap4bsWszBWxlBmB4TDSWM7SKZ3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card missing", "report lost card", "lost card action"]', role='assistant', function_call=None, tool_calls=None))], created=1715267007, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["card missing", "report lost card", "lost card action"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got my new card where do I go to activate it?"

Keyphrases:
2854it [1:36:21,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzarJUURdfL0lwrNbTUKqBXApmOp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate new card", "how to activate card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267009, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["card activation", "activate new card", "how to activate card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Would like to use my card and need to activate it first.  Can you help me do this?"

Keyphrases:
2855it [1:36:23,  1.86s/it]
ChatCompletion(id='chatcmpl-9Mzatz3gGnwKU18XbfZNJrbdfW3BU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "help with card activation"]', role='assistant', function_call=None, tool_calls=None))], created=1715267011, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=239, total_tokens=253))
["card activation", "activate card", "help with card activation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need help activating my new card."

Keyphrases:
2856it [1:36:24,  1.68s/it]
ChatCompletion(id='chatcmpl-9Mzav2cvnELcfywKWtA2oDLB4jqIl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "assistance with card activation"]', role='assistant', function_call=None, tool_calls=None))], created=1715267013, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["card activation", "activate card", "assistance with card activation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how to activate card?"

Keyphrases:
2857it [1:36:26,  1.94s/it]
ChatCompletion(id='chatcmpl-9MzawHOyesHIBMuj3pBafs7KMzHKD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "activate new card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267014, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["card activation", "activate card", "activate new card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please, activate my card"

Keyphrases:
2858it [1:36:28,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzazBoU2AkSwWzDx0F9cAVNpcBpX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "enable card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267017, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["card activation", "activate card", "enable card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I tried activating my bill of fare and it didn't workplace"

Keyphrases:
2859it [1:36:29,  1.60s/it]
ChatCompletion(id='chatcmpl-9Mzb0QLphKoyCLSQyxk4ZSUws6gAR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["bill activation", "activation failed", "service activation issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715267018, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["bill activation", "activation failed", "service activation issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I just got my card and want to use it, how do I activate my card?"

Keyphrases:
2860it [1:36:30,  1.52s/it]
ChatCompletion(id='chatcmpl-9Mzb1NaQu7vtuKwE7aRvCItkSdRlZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate new card", "how to activate card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267019, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["card activation", "activate new card", "how to activate card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have a new card and I want to activate it"

Keyphrases:
2861it [1:36:32,  1.46s/it]
ChatCompletion(id='chatcmpl-9Mzb3g0uZEqXorAdrLCciW1i1w7dm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate new card", "new card setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715267021, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["card activation", "activate new card", "new card setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Assist me please with card activation."

Keyphrases:
2862it [1:36:33,  1.42s/it]
ChatCompletion(id='chatcmpl-9Mzb4O3whz5EEpFsCLd4lj3SZdhE9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "card activation assistance"]', role='assistant', function_call=None, tool_calls=None))], created=1715267022, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card activation", "activate card", "card activation assistance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need help with activating my card"

Keyphrases:
2863it [1:36:34,  1.36s/it]
ChatCompletion(id='chatcmpl-9Mzb5j5BDCVjjWVnLsUXMsOyjCJ3s', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "assist card activation"]', role='assistant', function_call=None, tool_calls=None))], created=1715267023, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card activation", "activate card", "assist card activation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I start using my card?"

Keyphrases:
2864it [1:36:37,  1.75s/it]
ChatCompletion(id='chatcmpl-9Mzb6X65jRM2Kd0OqL8SzmYTfkfxW', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "start using card", "activate card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267024, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card activation", "start using card", "activate card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Activating my card"

Keyphrases:
2865it [1:36:39,  1.72s/it]
ChatCompletion(id='chatcmpl-9Mzb9wSb6wObH2Aayq6FOaxX4kNi6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "activating debit card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267027, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=223, total_tokens=237))
["card activation", "activate card", "activating debit card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When will my card be activated?"

Keyphrases:
2866it [1:36:40,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzbBBTdi3xSSaaRt7FKNET3i4OiS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "card activation time"]', role='assistant', function_call=None, tool_calls=None))], created=1715267029, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["card activation", "activate card", "card activation time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I activate my card>"

Keyphrases:
2867it [1:36:42,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzbCmQkK6S7E7QpsZZJP6r0zZy0H', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "how to activate"]', role='assistant', function_call=None, tool_calls=None))], created=1715267030, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card activation", "activate card", "how to activate"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the steps in order to activate my new card?"

Keyphrases:
2868it [1:36:44,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzbEDtZvIP8Fj3O0uWgeYfgjD9rd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "steps to activate card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267032, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["card activation", "activate card", "steps to activate card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I go about activating my new card?"

Keyphrases:
2869it [1:36:45,  1.65s/it]
ChatCompletion(id='chatcmpl-9MzbGXczOXY7zRR1ZKtDFBQ4mdxzT', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["activate card", "card activation process", "new card activation"]', role='assistant', function_call=None, tool_calls=None))], created=1715267034, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["activate card", "card activation process", "new card activation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the activation process on my new card?"

Keyphrases:
2870it [1:36:48,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzbHKLOhLZVDqMKJcUXPeXcg6Srn', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "activation process"]', role='assistant', function_call=None, tool_calls=None))], created=1715267035, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["card activation", "activate card", "activation process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to get help from someone with activating my card."

Keyphrases:
2871it [1:36:49,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzbK5BTavENDE3ugUss9qGQGevQ5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation assistance", "activate card", "help with card activation"]', role='assistant', function_call=None, tool_calls=None))], created=1715267038, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["card activation assistance", "activate card", "help with card activation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the process for activating my card?"

Keyphrases:
2872it [1:36:50,  1.63s/it]
ChatCompletion(id='chatcmpl-9MzbLV2O6nmcEja1ZVpKirlTTTyVp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "card activation process"]', role='assistant', function_call=None, tool_calls=None))], created=1715267039, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["card activation", "activate card", "card activation process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I use my new card?"

Keyphrases:
2873it [1:36:54,  2.12s/it]
ChatCompletion(id='chatcmpl-9MzbPaRSn40CxCGSilmT92kEEzCG1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["activate card", "card usage", "using new card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267043, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["activate card", "card usage", "using new card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got my new card but I am not sure if it need s activated and how?"

Keyphrases:
2874it [1:36:56,  2.10s/it]
ChatCompletion(id='chatcmpl-9MzbQuTYLE6xU3alvKB9xwswGkTH8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "how to activate card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267044, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=236, total_tokens=250))
["card activation", "activate card", "how to activate card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the steps to activating a new card?"

Keyphrases:
2875it [1:36:58,  2.16s/it]
ChatCompletion(id='chatcmpl-9MzbSOKyjlCUDPp3uoOuuDia8P6Lh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate new card", "how to activate card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267046, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["card activation", "activate new card", "how to activate card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to activate my card to use now, can you help me?"

Keyphrases:
2876it [1:37:00,  1.96s/it]
ChatCompletion(id='chatcmpl-9MzbU95kfIBwp9hjVHh7DcX5iEsy8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "immediate card use"]', role='assistant', function_call=None, tool_calls=None))], created=1715267048, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["card activation", "activate card", "immediate card use"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I activate a new card?"

Keyphrases:
2877it [1:37:01,  1.80s/it]
ChatCompletion(id='chatcmpl-9MzbWtYZ2siG40rraCRJKNdfzaJfP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "new card setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715267050, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["card activation", "activate card", "new card setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I just got this card & I don't know how to activate it."

Keyphrases:
2878it [1:37:02,  1.63s/it]
ChatCompletion(id='chatcmpl-9MzbXDZbZOdCgvXtdVoZb0SS71zwP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "how to activate card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267051, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["card activation", "activate card", "how to activate card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got my new card. How do I activate it?"

Keyphrases:
2879it [1:37:04,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzbYLz47RtSHGKiDcO8PPuNnEux7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate new card", "how to activate card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267052, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["card activation", "activate new card", "how to activate card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I need to do to activate my card?"

Keyphrases:
2880it [1:37:06,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzbaPH6NxSzLYMiG9DQRD3pQyuoy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card activation", "activate card", "how to activate card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267054, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["card activation", "activate card", "how to activate card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I see some fees for cash withdraw."

Keyphrases:
2881it [1:37:07,  1.58s/it]
ChatCompletion(id='chatcmpl-9MzbcmdcRU1eyUfbnzHdgLozSXlod', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal fees", "banking fees", "transaction fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715267056, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["cash withdrawal fees", "banking fees", "transaction fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How come I was charged extra when I withdrew cash?"

Keyphrases:
2882it [1:37:09,  1.63s/it]
ChatCompletion(id='chatcmpl-9MzbdGTcJHScPfuIZQ4H24YH5K5o5', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra charges", "cash withdrawal fee", "unexpected fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715267057, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["extra charges", "cash withdrawal fee", "unexpected fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why am I being charged when I withdraw cash?"

Keyphrases:
2883it [1:37:10,  1.66s/it]
ChatCompletion(id='chatcmpl-9Mzbf68lIQdn0XviyqMX5V1UBHs0u', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal fee", "cash withdrawal charge", "banking fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715267059, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["ATM withdrawal fee", "cash withdrawal charge", "banking fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is this charge on my account for a cash withdrawl?"

Keyphrases:
2884it [1:37:12,  1.62s/it]
ChatCompletion(id='chatcmpl-9MzbhOIG4PrM2VYEsRIdfY26Lg98k', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unexplained charge", "cash withdrawal query", "account charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715267061, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["unexplained charge", "cash withdrawal query", "account charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why are fees charged on cash withdrawals? I went to withdraw some money earlier today after shopping. There's a fee that wasn't there before."

Keyphrases:
2885it [1:37:14,  1.60s/it]
ChatCompletion(id='chatcmpl-9MzbikXmyJ5H2VL8HlWFzAfxxPzIL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal fees", "ATM fees", "transaction fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715267062, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=247, total_tokens=261))
["cash withdrawal fees", "ATM fees", "transaction fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How come you charge for cash withdrawals? I withdrew cash after buying groceries today, and there seems to be a new fee"

Keyphrases:
2886it [1:37:15,  1.49s/it]
ChatCompletion(id='chatcmpl-9MzbkfGKP3yl5L6XXJhV4ioknZWgi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal fees", "transaction fees", "withdrawal charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715267064, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=243, total_tokens=257))
["cash withdrawal fees", "transaction fees", "withdrawal charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It looks like I was charged a withdrawal fee for going to my ATM. Why is that because I haven't been charged previously for doing so?"

Keyphrases:
2887it [1:37:16,  1.44s/it]
ChatCompletion(id='chatcmpl-9MzblIBVlktpK4KYgsxqpAjbgtcxY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal fee", "unexpected charges", "fee inquiry"]', role='assistant', function_call=None, tool_calls=None))], created=1715267065, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=247, total_tokens=261))
["ATM withdrawal fee", "unexpected charges", "fee inquiry"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do ATM cash withdrawals carry a charge now? They've been free in the past, but all of a sudden I have to pay to make ATM withdrawals?"

Keyphrases:
2888it [1:37:18,  1.53s/it]
ChatCompletion(id='chatcmpl-9Mzbm0QsHUpXaoEQ53EavFFoqj1cB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal fees", "charges on ATM withdrawals", "change in ATM fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715267066, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=249, total_tokens=267))
["ATM withdrawal fees", "charges on ATM withdrawals", "change in ATM fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is there an extra charge for money that was withdrawn?"

Keyphrases:
2889it [1:37:20,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzboWFfz9KGvQtgfqS4l5XWnhh38', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra charge", "withdrawal fees", "unexplained fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715267068, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["extra charge", "withdrawal fees", "unexplained fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was I charged a fee for withdrawing cash?"

Keyphrases:
2890it [1:37:21,  1.63s/it]
ChatCompletion(id='chatcmpl-9Mzbq8otacBCFsfRgdFMpyK6zlqge', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal fee", "ATM fee", "bank charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715267070, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["withdrawal fee", "ATM fee", "bank charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I get a fee?"

Keyphrases:
2891it [1:37:23,  1.51s/it]
ChatCompletion(id='chatcmpl-9MzbsWZyhm7lrmuDG9hc9NrOOdOID', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["banking fee", "fee explanation", "unexpected charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715267072, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["banking fee", "fee explanation", "unexpected charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did my cash get charged a fee that should not be there."

Keyphrases:
2892it [1:37:24,  1.55s/it]
ChatCompletion(id='chatcmpl-9Mzbtle5UDFHy2e3RoLBwfXGhiZX7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["unjustified fee", "unexpected fee", "cash transaction fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715267073, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=232, total_tokens=247))
["unjustified fee", "unexpected fee", "cash transaction fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I have to pay a fee when I got cash?"

Keyphrases:
2893it [1:37:30,  2.65s/it]
ChatCompletion(id='chatcmpl-9MzbvtpPAicqFB4UZiK8PcmCpsXIp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["banking fee", "withdrawal fee", "cash transaction fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715267075, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["banking fee", "withdrawal fee", "cash transaction fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Hi, I am calling about a recent transaction that has happened on my account.  I recently went to the ATM, and tried to make a withdrawal on my account.  I just happened to check my transaction slip and noticed a fee for my withdrawal.  How can I resolve this, I didn't know fees were charged for this type of action."

Keyphrases:
2894it [1:37:31,  2.25s/it]
ChatCompletion(id='chatcmpl-9Mzc0Shrf2gA66VSB7Q23Rpwr9tuq', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal fee", "unexpected fee", "fee dispute"]', role='assistant', function_call=None, tool_calls=None))], created=1715267080, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=289, total_tokens=303))
["ATM withdrawal fee", "unexpected fee", "fee dispute"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "A fee was charged for my recent withdrawal."

Keyphrases:
2895it [1:37:32,  2.04s/it]
ChatCompletion(id='chatcmpl-9Mzc1X09Qd67HMTBTBQbJXf32nUFr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal fee", "fee complaint"]', role='assistant', function_call=None, tool_calls=None))], created=1715267081, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=9, prompt_tokens=227, total_tokens=236))
["withdrawal fee", "fee complaint"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got a fee for an ATM withdrawal."

Keyphrases:
2896it [1:37:34,  1.83s/it]
ChatCompletion(id='chatcmpl-9Mzc3wUI2S6h5iOVsBvEhW15gx8Hx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal fee", "banking fees", "fee complaint"]', role='assistant', function_call=None, tool_calls=None))], created=1715267083, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["ATM withdrawal fee", "banking fees", "fee complaint"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the reason for this fee I got after a simple cash withdrawal?"

Keyphrases:
2897it [1:37:35,  1.80s/it]
ChatCompletion(id='chatcmpl-9Mzc43ELQGeqJ8UKTYMs3n3IJlkVH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal fee", "transaction charges", "unexplained fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715267084, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["withdrawal fee", "transaction charges", "unexplained fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Did you start charging for cash withdrawals? I thought it was free so far but noticed suddendly there is a fee. How much do I need to pay?"

Keyphrases:
2898it [1:37:37,  1.81s/it]
ChatCompletion(id='chatcmpl-9Mzc6oRTf9xDYKSWxl9mk0eiOvgmx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal fee", "withdrawal charges", "fee query"]', role='assistant', function_call=None, tool_calls=None))], created=1715267086, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=252, total_tokens=266))
["cash withdrawal fee", "withdrawal charges", "fee query"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a fee for withdrawing cash?"

Keyphrases:
2899it [1:37:40,  2.10s/it]
ChatCompletion(id='chatcmpl-9Mzc8PXsvobdutov5nkeki5nE4Mdc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal fee", "ATM charges", "banking fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715267088, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=226, total_tokens=241))
["cash withdrawal fee", "ATM charges", "banking fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I've notice I was charged for withdrawing cash, can you explain why?"

Keyphrases:
2900it [1:37:43,  2.48s/it]
ChatCompletion(id='chatcmpl-9MzcAqQLfIUkpRB5FMIExpWOENfgt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal fee", "cash withdrawal charge", "transaction fee explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715267090, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["withdrawal fee", "cash withdrawal charge", "transaction fee explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why was my account charged for using an ATM?"

Keyphrases:
2901it [1:37:46,  2.38s/it]
ChatCompletion(id='chatcmpl-9MzcEbJGJv7fE10ILUdHS72EM9TED', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM charge query", "bank fee explanation", "account charge reasons"]', role='assistant', function_call=None, tool_calls=None))], created=1715267094, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["ATM charge query", "bank fee explanation", "account charge reasons"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is there a charge on my account for taking out cash?"

Keyphrases:
2902it [1:37:48,  2.35s/it]
ChatCompletion(id='chatcmpl-9MzcGXVN51BAFBGjzG7ve5jvCFBEX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM withdrawal fee", "bank charges", "unexpected charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715267096, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["ATM withdrawal fee", "bank charges", "unexpected charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "An ATM fee was attached to my recent withdrawal."

Keyphrases:
2903it [1:37:49,  2.10s/it]
ChatCompletion(id='chatcmpl-9MzcIOS9lLInzyFyvcC5A0Woet8dM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM fee", "withdrawal fee", "unexpected fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715267098, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["ATM fee", "withdrawal fee", "unexpected fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I thought cash withdrawals didn't have a fee"

Keyphrases:
2904it [1:37:51,  2.00s/it]
ChatCompletion(id='chatcmpl-9MzcKP0iny5CnSIQb50HEP9Z4JMnC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal fee", "fee complaint", "withdrawal charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715267100, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["cash withdrawal fee", "fee complaint", "withdrawal charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did I get charged a fee when I tried to obtain cash?"

Keyphrases:
2905it [1:37:53,  1.98s/it]
ChatCompletion(id='chatcmpl-9MzcMq99Iu248S46jkiH6s9Bd3YmC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal fee", "transaction fee", "bank charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715267102, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["cash withdrawal fee", "transaction fee", "bank charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "While I was checking out in the grocery store, I realized I needed cash so I requested some.  However, I noticed there was a fee for this transaction.  Why did I get charged a fee?"

Keyphrases:
2906it [1:37:55,  1.95s/it]
ChatCompletion(id='chatcmpl-9MzcNkKclbo40omwe8grtjfvd6Hld', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash back fee", "transaction fee", "service charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715267103, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=260, total_tokens=273))
["cash back fee", "transaction fee", "service charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Using an ATM caused me to incur an additional fee. Why?"

Keyphrases:
2907it [1:37:57,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzcQ4I6pdq5ZxFoERj0Q43mpnO6l', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM fee", "additional charges", "fee explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715267106, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["ATM fee", "additional charges", "fee explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was charged extra for a withdrawal"

Keyphrases:
2908it [1:37:58,  1.69s/it]
ChatCompletion(id='chatcmpl-9MzcRQ7hybCD42sxt0H73x20RRjr9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["extra charges", "withdrawal fees", "incorrect charge"]', role='assistant', function_call=None, tool_calls=None))], created=1715267107, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["extra charges", "withdrawal fees", "incorrect charge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a limit on how much I can withdraw from my account without being charged?"

Keyphrases:
2909it [1:38:00,  1.70s/it]
ChatCompletion(id='chatcmpl-9MzcS8B7S5jwxyekd89mpcUmkhqEu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal limit", "account charges", "withdrawal fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715267108, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=235, total_tokens=249))
["withdrawal limit", "account charges", "withdrawal fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I thought cash withdrawals were free? Why have I been charged a fee? Also, how much is this fee?"

Keyphrases:
2910it [1:38:01,  1.74s/it]
ChatCompletion(id='chatcmpl-9MzcUhCDdbTcbX8peYksSEFjF1M86', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal fee", "withdrawal charges", "fee explanation"]', role='assistant', function_call=None, tool_calls=None))], created=1715267110, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=241, total_tokens=255))
["cash withdrawal fee", "withdrawal charges", "fee explanation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "More fees, this time for withdrawing my own cash. Why are you robbing me?"

Keyphrases:
2911it [1:38:05,  2.39s/it]
ChatCompletion(id='chatcmpl-9MzcXuh03IP12HxTCMMri3D163Cdb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal fees", "fee complaint", "banking fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715267113, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=236, total_tokens=250))
["withdrawal fees", "fee complaint", "banking fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I have never been charged a fee for cash withdrawal before. When did that change?"

Keyphrases:
2912it [1:38:07,  2.14s/it]
ChatCompletion(id='chatcmpl-9MzcaB9a3DoeBMZZ415uv6ovSmeeR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal fee", "fee policy change", "banking fees"]', role='assistant', function_call=None, tool_calls=None))], created=1715267116, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=235, total_tokens=250))
["cash withdrawal fee", "fee policy change", "banking fees"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I was charged for a cash withdrawal."

Keyphrases:
2913it [1:38:09,  2.08s/it]
ChatCompletion(id='chatcmpl-9MzcbimXzJn3V6rwlgNbxzOU1Aw0y', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal charge", "unauthorized charge", "ATM withdrawal fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715267117, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["cash withdrawal charge", "unauthorized charge", "ATM withdrawal fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why did you charge me for a cash withdrawal?"

Keyphrases:
2914it [1:38:11,  2.13s/it]
ChatCompletion(id='chatcmpl-9MzceCY2sl48xKTog6llLWzQ7NkQY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal charge", "fee explanation", "unexplained charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715267120, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["cash withdrawal charge", "fee explanation", "unexplained charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I took cash and got charged a fee"

Keyphrases:
2915it [1:38:13,  2.08s/it]
ChatCompletion(id='chatcmpl-9Mzcfp4FCPkDckqM7X3HKg4W9S0ew', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM fee", "withdrawal charge", "cash transaction fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715267121, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["ATM fee", "withdrawal charge", "cash transaction fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Was charged an ATM fee despite it being a small withdrawal on the 1st day of the month. I thought I was allowed 200 per month?"

Keyphrases:
2916it [1:38:15,  1.98s/it]
ChatCompletion(id='chatcmpl-9Mzcha9PRyr4GIJGdTSGYNTNV8QBS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM fee issue", "fee waiver conditions", "withdrawal limits"]', role='assistant', function_call=None, tool_calls=None))], created=1715267123, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=249, total_tokens=265))
["ATM fee issue", "fee waiver conditions", "withdrawal limits"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I had a wrong fee charged at this ATM."

Keyphrases:
2917it [1:38:16,  1.79s/it]
ChatCompletion(id='chatcmpl-9MzcjJyRYk0ncTbSWeEjo13kKdfiz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["incorrect fee", "ATM charge issue", "dispute fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715267125, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["incorrect fee", "ATM charge issue", "dispute fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When I got cash, I'm pretty sure there was a glitch that overcharged me."

Keyphrases:
2918it [1:38:18,  1.71s/it]
ChatCompletion(id='chatcmpl-9MzckwbKYXggC7gejZcYuDuojxwZb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ATM overcharge", "cash withdrawal issue", "transaction error"]', role='assistant', function_call=None, tool_calls=None))], created=1715267126, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=236, total_tokens=251))
["ATM overcharge", "cash withdrawal issue", "transaction error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My account got charged for taking out cash, why did this happen?"

Keyphrases:
2919it [1:38:19,  1.59s/it]
ChatCompletion(id='chatcmpl-9Mzcmm5sPQal07i2hEc2LJjnGLW2K', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["cash withdrawal charge", "account fee", "unexpected charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715267128, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["cash withdrawal charge", "account fee", "unexpected charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why is there a fee for withdrawing?"

Keyphrases:
2920it [1:38:21,  1.73s/it]
ChatCompletion(id='chatcmpl-9Mzcnk89GIe6pWDH29u3TBHd4xFTN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["withdrawal fee", "fee query", "bank charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715267129, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["withdrawal fee", "fee query", "bank charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Am I able to order a new card and have it sent to me in China?"

Keyphrases:
2921it [1:38:23,  1.67s/it]
ChatCompletion(id='chatcmpl-9Mzcp6wPWyqg86KNkX5ZknLHSBT7W', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["order new card", "card delivery international", "shipping to China"]', role='assistant', function_call=None, tool_calls=None))], created=1715267131, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=235, total_tokens=250))
["order new card", "card delivery international", "shipping to China"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will you be able to send the new card to China?"

Keyphrases:
2922it [1:38:25,  1.79s/it]
ChatCompletion(id='chatcmpl-9MzcrfpLXaRlVxEj8sjV0ynCPfe3b', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["new card delivery", "international card shipping", "card shipment overseas"]', role='assistant', function_call=None, tool_calls=None))], created=1715267133, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["new card delivery", "international card shipping", "card shipment overseas"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When my card expires what happens to my account?"

Keyphrases:
2923it [1:38:26,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzctZXIAvZLZQygAQV6iiFGiKJba', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiry", "account status post-expiry", "effects of card expiration"]', role='assistant', function_call=None, tool_calls=None))], created=1715267135, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["card expiry", "account status post-expiry", "effects of card expiration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do when my card expires?"

Keyphrases:
2924it [1:38:29,  2.07s/it]
ChatCompletion(id='chatcmpl-9MzcutoksNHe3VtdhDuWiHESnVSxg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiration", "renew expired card", "expired card action"]', role='assistant', function_call=None, tool_calls=None))], created=1715267136, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["card expiration", "renew expired card", "expired card action"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The expiration date on my card is coming up"

Keyphrases:
2925it [1:38:34,  2.88s/it]
ChatCompletion(id='chatcmpl-9MzcxFxS9hhQnzO79yHOKwKPojbJm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiration", "renew card", "expiration date"]', role='assistant', function_call=None, tool_calls=None))], created=1715267139, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["card expiration", "renew card", "expiration date"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card's expiring, what happens now?"

Keyphrases:
2926it [1:38:36,  2.64s/it]
ChatCompletion(id='chatcmpl-9Mzd2O3zSy5aLCo1riTl6e456KspU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiration", "renew card", "expired card process"]', role='assistant', function_call=None, tool_calls=None))], created=1715267144, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["card expiration", "renew card", "expired card process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is about to expire. What do I need to do?"

Keyphrases:
2927it [1:38:37,  2.23s/it]
ChatCompletion(id='chatcmpl-9Mzd4c5vzDR94vvg2Bij6cWKlLrDe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiration", "renew card", "expiration procedure"]', role='assistant', function_call=None, tool_calls=None))], created=1715267146, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["card expiration", "renew card", "expiration procedure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how long and how much does it cost for new card"

Keyphrases:
2928it [1:38:39,  2.04s/it]
ChatCompletion(id='chatcmpl-9Mzd5dg6OnMOWDIqOTWGdlQitMZ8R', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["new card cost", "new card duration", "card issuance fee"]', role='assistant', function_call=None, tool_calls=None))], created=1715267147, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["new card cost", "new card duration", "card issuance fee"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do if my card is expiring soon?"

Keyphrases:
2929it [1:38:40,  1.92s/it]
ChatCompletion(id='chatcmpl-9Mzd7uP9LxdAI0VFiAkeOzbehemm3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiration", "renew card", "expiring card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267149, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["card expiration", "renew card", "expiring card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How much does it cost to get a new card?  Mine is almost expired.  How fast does it come?"

Keyphrases:
2930it [1:38:42,  1.97s/it]
ChatCompletion(id='chatcmpl-9Mzd9i1H5th2QKD0EyCY9n40Ibub4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card replacement cost", "card expiry", "replacement card delivery time"]', role='assistant', function_call=None, tool_calls=None))], created=1715267151, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=15, prompt_tokens=242, total_tokens=257))
["card replacement cost", "card expiry", "replacement card delivery time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Since my card is about to expire, what do I do to get a new one?"

Keyphrases:
2931it [1:38:44,  1.81s/it]
ChatCompletion(id='chatcmpl-9MzdBsBxeXVDmY5oVJ41ma3hd1bzM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card renewal", "expired card", "replace card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267153, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=236, total_tokens=248))
["card renewal", "expired card", "replace card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is about to expire and I need to know how much it costs and how long it takes to get a new one."

Keyphrases:
2932it [1:38:48,  2.49s/it]
ChatCompletion(id='chatcmpl-9MzdCYmLzJf8v6lFEHuViEmpsgXRC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card renewal", "replacement cost", "replacement time"]', role='assistant', function_call=None, tool_calls=None))], created=1715267154, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=244, total_tokens=256))
["card renewal", "replacement cost", "replacement time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When my card expires do you send a new card?"

Keyphrases:
2933it [1:38:50,  2.45s/it]
ChatCompletion(id='chatcmpl-9MzdGnI0VQh7epBvw80he9UE9Iovm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiration", "card renewal", "automatic renewal"]', role='assistant', function_call=None, tool_calls=None))], created=1715267158, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["card expiration", "card renewal", "automatic renewal"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is the next step if my card is about to expire."

Keyphrases:
2934it [1:38:52,  2.14s/it]
ChatCompletion(id='chatcmpl-9MzdJgkkDJWQ3z2paQk5DdoMqR1BU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiration", "renew card", "next steps for expiring card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267161, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["card expiration", "renew card", "next steps for expiring card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Once my card expires, what should I do?"

Keyphrases:
2935it [1:38:54,  2.11s/it]
ChatCompletion(id='chatcmpl-9MzdK2Yny16FfD6IzKVBvGKqQlcbj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiration", "renew expired card", "expired card actions"]', role='assistant', function_call=None, tool_calls=None))], created=1715267162, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=228, total_tokens=243))
["card expiration", "renew expired card", "expired card actions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need a new card, my current card is nearly expired."

Keyphrases:
2936it [1:38:55,  1.94s/it]
ChatCompletion(id='chatcmpl-9MzdMxinyvhLshMhCQlGGDPXhoJv9', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card renewal", "expired card", "request new card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267164, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["card renewal", "expired card", "request new card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "It appears my card expires next month, can I order a new one?"

Keyphrases:
2937it [1:38:57,  1.94s/it]
ChatCompletion(id='chatcmpl-9MzdOBLDAqQ0Ve8xFCyJxSsuVayVM', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card renewal", "new card request", "card expiration"]', role='assistant', function_call=None, tool_calls=None))], created=1715267166, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["card renewal", "new card request", "card expiration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is about to expire. How much does it cost to order a new one and how fast will I get it?"

Keyphrases:
2938it [1:38:59,  1.75s/it]
ChatCompletion(id='chatcmpl-9MzdQHk4Oe4geIAZGCG3ZhK1KIj5Q', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card renewal", "card expiration", "replacement cost", "delivery time"]', role='assistant', function_call=None, tool_calls=None))], created=1715267168, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=243, total_tokens=259))
["card renewal", "card expiration", "replacement cost", "delivery time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do when my card is about to expire?"

Keyphrases:
2939it [1:39:01,  1.84s/it]
ChatCompletion(id='chatcmpl-9MzdRdrOSNa4NdJDnttTu5fbMCxJJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiration", "renew card", "expiration date"]', role='assistant', function_call=None, tool_calls=None))], created=1715267169, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["card expiration", "renew card", "expiration date"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I will need to get a new card soon, how do I order?"

Keyphrases:
2940it [1:39:02,  1.66s/it]
ChatCompletion(id='chatcmpl-9MzdTBVFkVDRnoEEAplWPiBx3FuYl', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["order new card", "replacement card", "card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715267171, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["order new card", "replacement card", "card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "going to need a new card what are the fees and time it takes"

Keyphrases:
2941it [1:39:03,  1.59s/it]
ChatCompletion(id='chatcmpl-9MzdU8UMKxyDZrpgpMRSu3WHa4GXx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["new card request", "card replacement fees", "replacement duration"]', role='assistant', function_call=None, tool_calls=None))], created=1715267172, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["new card request", "card replacement fees", "replacement duration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Will I need to order a new card since mine expires next month?"

Keyphrases:
2942it [1:39:05,  1.58s/it]
ChatCompletion(id='chatcmpl-9MzdW8zBqlY5N6V0VPmuezXPKc62C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card renewal", "new card request", "card expiration"]', role='assistant', function_call=None, tool_calls=None))], created=1715267174, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["card renewal", "new card request", "card expiration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When my card expires, will I get a new one mailed to me?"

Keyphrases:
2943it [1:39:07,  1.72s/it]
ChatCompletion(id='chatcmpl-9MzdX743a0dslNTmyyMgdK3KwMP4T', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiration", "card renewal", "new card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715267175, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["card expiration", "card renewal", "new card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you have to order a new card before your current card expires?"

Keyphrases:
2944it [1:39:08,  1.57s/it]
ChatCompletion(id='chatcmpl-9MzdZ9dhK44rK1y00AQZzTanDldkg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card renewal", "expiry date", "new card order"]', role='assistant', function_call=None, tool_calls=None))], created=1715267177, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["card renewal", "expiry date", "new card order"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Since my card is about to expire, I need a new one."

Keyphrases:
2945it [1:39:10,  1.59s/it]
ChatCompletion(id='chatcmpl-9MzdaLKlQ1goibt2IXhrT2dYIosIe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card renewal", "expired card replacement", "reissue card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267178, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["card renewal", "expired card replacement", "reissue card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is very close to expiring. When can I order a new one and how do I do so?"

Keyphrases:
2946it [1:39:11,  1.45s/it]
ChatCompletion(id='chatcmpl-9MzdcHg713Z5YQFE8yjSuGSoDhy30', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card renewal", "order new card", "card expiration"]', role='assistant', function_call=None, tool_calls=None))], created=1715267180, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=241, total_tokens=254))
["card renewal", "order new card", "card expiration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to order a  new card, mine is about to expire and I need to know how much it will cost and how long until I receive it."

Keyphrases:
2947it [1:39:13,  1.57s/it]
ChatCompletion(id='chatcmpl-9MzddrrxgJjffDeOr69TN1wXQJ46z', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["new card order", "card expiration", "card replacement cost", "replacement delivery time"]', role='assistant', function_call=None, tool_calls=None))], created=1715267181, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=19, prompt_tokens=250, total_tokens=269))
["new card order", "card expiration", "card replacement cost", "replacement delivery time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I order a new card before It expires?"

Keyphrases:
2948it [1:39:14,  1.59s/it]
ChatCompletion(id='chatcmpl-9MzdfrMCpxCuoq4FBbkHGbCBY2P6K', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["reorder card", "card expiration", "new card request"]', role='assistant', function_call=None, tool_calls=None))], created=1715267183, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["reorder card", "card expiration", "new card request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I receive a new card while I am in China?"

Keyphrases:
2949it [1:39:16,  1.64s/it]
ChatCompletion(id='chatcmpl-9MzdhMSEdjAaokHxmLfgxnZbGpYUd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international card issuance", "new card abroad", "replace card overseas"]', role='assistant', function_call=None, tool_calls=None))], created=1715267185, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["international card issuance", "new card abroad", "replace card overseas"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Next month my card will expire, do I need to order a new one?"

Keyphrases:
2950it [1:39:18,  1.79s/it]
ChatCompletion(id='chatcmpl-9MzdiGeAOiFSPYPygYZPQDkFJMa8T', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiration", "renew card", "new card order"]', role='assistant', function_call=None, tool_calls=None))], created=1715267186, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=234, total_tokens=248))
["card expiration", "renew card", "new card order"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "The expiration date of my card is approaching ."

Keyphrases:
2951it [1:39:19,  1.62s/it]
ChatCompletion(id='chatcmpl-9Mzdl4ne9YztteU4GUQUYCH7V7pcb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiration", "renew card", "expiration date"]', role='assistant', function_call=None, tool_calls=None))], created=1715267189, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["card expiration", "renew card", "expiration date"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I get a new card ASAP to replace an old, soon to expire one?"

Keyphrases:
2952it [1:39:22,  1.87s/it]
ChatCompletion(id='chatcmpl-9Mzdm5sWFkXIfBaoGdOns3n9QLniU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["replacement card", "expiring card", "urgent card replacement"]', role='assistant', function_call=None, tool_calls=None))], created=1715267190, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=236, total_tokens=250))
["replacement card", "expiring card", "urgent card replacement"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need a new card since my old one is about to expire."

Keyphrases:
2953it [1:39:23,  1.71s/it]
ChatCompletion(id='chatcmpl-9MzdovA4gs8xdQtVebkIS5vCODrJZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card renewal", "expired card", "request new card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267192, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["card renewal", "expired card", "request new card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is about to expire."

Keyphrases:
2954it [1:39:25,  1.60s/it]
ChatCompletion(id='chatcmpl-9MzdqA3JhaPoOYFP7vAo9Neg2jhTy', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card expiration", "renew card", "expiry date"]', role='assistant', function_call=None, tool_calls=None))], created=1715267194, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["card expiration", "renew card", "expiry date"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is expiring shortly.  How much will it cost for a replacement, and how soon can I get it?"

Keyphrases:
2955it [1:39:26,  1.63s/it]
ChatCompletion(id='chatcmpl-9Mzdrmy9vRdskBvkiE3EoWNKA5hQ1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card replacement cost", "card expiry", "replacement timeline"]', role='assistant', function_call=None, tool_calls=None))], created=1715267195, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=243, total_tokens=256))
["card replacement cost", "card expiry", "replacement timeline"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What would the price be for an expired card replacement and how long will it take me to get it?"

Keyphrases:
2956it [1:39:28,  1.55s/it]
ChatCompletion(id='chatcmpl-9MzdtaHNnVMEsgP37c2eJNleqWngP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card replacement cost", "expired card", "replacement duration"]', role='assistant', function_call=None, tool_calls=None))], created=1715267197, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=239, total_tokens=252))
["card replacement cost", "expired card", "replacement duration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "in china, need new card"

Keyphrases:
2957it [1:39:30,  1.76s/it]
ChatCompletion(id='chatcmpl-9Mzdu7AYXePvg8Skvawp33nA0y8Zt', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card replacement", "new card request", "issue new card abroad"]', role='assistant', function_call=None, tool_calls=None))], created=1715267198, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=225, total_tokens=240))
["card replacement", "new card request", "issue new card abroad"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If my card is about to expire, do I need to order a new one?"

Keyphrases:
2958it [1:39:32,  1.78s/it]
ChatCompletion(id='chatcmpl-9MzdwkQukliqYHlyBQk2UMqQbzPIf', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card renewal", "expiration", "new card request"]', role='assistant', function_call=None, tool_calls=None))], created=1715267200, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=235, total_tokens=247))
["card renewal", "expiration", "new card request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My card is about to expire. How do I get a new one?"

Keyphrases:
2959it [1:39:34,  2.02s/it]
ChatCompletion(id='chatcmpl-9MzdyW17vmTyYDeb31nbVthD92CO7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card renewal", "expire card", "new card request"]', role='assistant', function_call=None, tool_calls=None))], created=1715267202, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=13, prompt_tokens=233, total_tokens=246))
["card renewal", "expire card", "new card request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to know the cost and when I will receive a new card to replace an old one."

Keyphrases:
2960it [1:39:36,  1.84s/it]
ChatCompletion(id='chatcmpl-9Mze1s0X0D3J0sDKMWXuiIioxDYVd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card replacement cost", "replacement card delivery time"]', role='assistant', function_call=None, tool_calls=None))], created=1715267205, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=11, prompt_tokens=238, total_tokens=249))
["card replacement cost", "replacement card delivery time"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is the top up feature available on the Apple Watch?"

Keyphrases:
2961it [1:39:37,  1.69s/it]
ChatCompletion(id='chatcmpl-9Mze2YQF9e13ozjt7NFrEwxIW9OIg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up feature", "device compatibility", "Apple Watch services"]', role='assistant', function_call=None, tool_calls=None))], created=1715267206, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["top up feature", "device compatibility", "Apple Watch services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use the system Google Pay for top-ups?"

Keyphrases:
2962it [1:39:39,  1.70s/it]
ChatCompletion(id='chatcmpl-9Mze3NLeIF3eBOABWnOlL6OKKfDWb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Google Pay usage", "top-ups via Google Pay", "digital wallet top-up compatibility"]', role='assistant', function_call=None, tool_calls=None))], created=1715267207, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=19, prompt_tokens=229, total_tokens=248))
["Google Pay usage", "top-ups via Google Pay", "digital wallet top-up compatibility"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top-up for Google Pay isn't working"

Keyphrases:
2963it [1:39:41,  1.93s/it]
ChatCompletion(id='chatcmpl-9Mze59cmeWoXozGZYUxpDvr88Cr2c', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Google Pay top-up issue", "payment failure", "mobile wallet top-up problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715267209, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=228, total_tokens=246))
["Google Pay top-up issue", "payment failure", "mobile wallet top-up problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I add money with Apple Pay?"

Keyphrases:
2964it [1:39:46,  2.69s/it]
ChatCompletion(id='chatcmpl-9Mze83K6W94tUqWxGd3qvempeLoqC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["add money", "Apple Pay", "funding options"]', role='assistant', function_call=None, tool_calls=None))], created=1715267212, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["add money", "Apple Pay", "funding options"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use my Apple Watch to to top up?"

Keyphrases:
2965it [1:39:50,  3.06s/it]
ChatCompletion(id='chatcmpl-9MzeCOpzspTLY57N6Ij9q6cfX1uHj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["smartwatch banking", "top up using wearables", "Apple Watch transaction"]', role='assistant', function_call=None, tool_calls=None))], created=1715267216, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["smartwatch banking", "top up using wearables", "Apple Watch transaction"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Does Apple Pay give the option to top up?"

Keyphrases:
2966it [1:39:53,  3.04s/it]
ChatCompletion(id='chatcmpl-9MzeG8mCW4TjDv2657ZVhI0B1WAHF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Apple Pay top up", "mobile wallet funding", "digital wallet reload"]', role='assistant', function_call=None, tool_calls=None))], created=1715267220, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["Apple Pay top up", "mobile wallet funding", "digital wallet reload"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Top up on my Google Pay isn't working."

Keyphrases:
2967it [1:39:54,  2.65s/it]
ChatCompletion(id='chatcmpl-9MzeJ4WB3WJMFrhU8CLr3zjYJwi26', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Google Pay top up issue", "payment failure", "mobile wallet top up problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715267223, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=18, prompt_tokens=228, total_tokens=246))
["Google Pay top up issue", "payment failure", "mobile wallet top up problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to top up with Apple Pay?"

Keyphrases:
2968it [1:39:56,  2.31s/it]
ChatCompletion(id='chatcmpl-9MzeLfqwCEAmhcY4eUBIR8nRsUH31', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Apple Pay top up", "wallet reload", "payment methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715267225, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["Apple Pay top up", "wallet reload", "payment methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "do i have to setup apple pay to use it"

Keyphrases:
2969it [1:39:58,  2.33s/it]
ChatCompletion(id='chatcmpl-9MzeMAfcC5vN8nMEqVWNcB7kFkRCb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["apple pay setup", "setting up apple pay", "apple pay requirements"]', role='assistant', function_call=None, tool_calls=None))], created=1715267226, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["apple pay setup", "setting up apple pay", "apple pay requirements"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use Apple Pay to top up?"

Keyphrases:
2970it [1:40:00,  2.24s/it]
ChatCompletion(id='chatcmpl-9MzeP85jEmwhFz7igAUzTUb9POikd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Apple Pay usage", "top up with Apple Pay", "digital wallet top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715267229, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=227, total_tokens=245))
["Apple Pay usage", "top up with Apple Pay", "digital wallet top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I top up my Google Pay?"

Keyphrases:
2971it [1:40:02,  2.10s/it]
ChatCompletion(id='chatcmpl-9MzeRs9vAVQKdJrHwqreA4l4rDQpV', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up", "Google Pay reload", "add money to Google Pay"]', role='assistant', function_call=None, tool_calls=None))], created=1715267231, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["top up", "Google Pay reload", "add money to Google Pay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Does Google Play have an app to Top up?"

Keyphrases:
2972it [1:40:05,  2.28s/it]
ChatCompletion(id='chatcmpl-9MzeSLIFuUYzK2sMf43m6j3WNGzvr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["app top up", "Google Play top up", "banking app recharge"]', role='assistant', function_call=None, tool_calls=None))], created=1715267232, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=17, prompt_tokens=228, total_tokens=245))
["app top up", "Google Play top up", "banking app recharge"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I received my American Express card, but I am having problems making it work with Apple pay.  Can you help me with this problem?"

Keyphrases:
2973it [1:40:12,  3.88s/it]
ChatCompletion(id='chatcmpl-9MzeVZQ5AbqnqfkPRuOhjBdRVhE77', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Apple Pay setup", "card compatibility", "American Express issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715267235, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=14, prompt_tokens=246, total_tokens=260))
["Apple Pay setup", "card compatibility", "American Express issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "is apple pay eligible for top up"

Keyphrases:
2974it [1:40:17,  4.15s/it]
ChatCompletion(id='chatcmpl-9MzedOmbL3WVgxHZA1w0y7wSZOzG8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["apple pay eligibility", "top up options", "digital wallet top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715267243, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=226, total_tokens=242))
["apple pay eligibility", "top up options", "digital wallet top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why can't I use my American Express with Apple Pay to top up my account?"

Keyphrases:
2975it [1:40:19,  3.47s/it]
ChatCompletion(id='chatcmpl-9MzehsZ88HLBjYZBpxBlI8a1UOm8f', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["American Express compatibility", "Apple Pay top-up", "account top-up issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715267247, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=235, total_tokens=252))
["American Express compatibility", "Apple Pay top-up", "account top-up issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how do i add money with my apple watch"

Keyphrases:
2976it [1:40:20,  2.83s/it]
ChatCompletion(id='chatcmpl-9MzejMat6J8Oi5X9rArg4WFOR8uU4', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["add money", "Apple Watch banking", "mobile wallet deposit"]', role='assistant', function_call=None, tool_calls=None))], created=1715267249, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["add money", "Apple Watch banking", "mobile wallet deposit"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If I want to top up, can I use Apple Pay?"

Keyphrases:
2977it [1:40:22,  2.50s/it]
ChatCompletion(id='chatcmpl-9Mzelk5qNQZoeGH6kXsNjtg01gRdg', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up options", "using Apple Pay", "payment methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715267251, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["top up options", "using Apple Pay", "payment methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "can i top up with apple pay"

Keyphrases:
2978it [1:40:24,  2.40s/it]
ChatCompletion(id='chatcmpl-9Mzemc2dQmyhriGNvYkBuSVzcVDFo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["apple pay top up", "mobile payment", "add money"]', role='assistant', function_call=None, tool_calls=None))], created=1715267252, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["apple pay top up", "mobile payment", "add money"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My American express is experiencing a problem with apple play with top up, can you fix it?"

Keyphrases:
2979it [1:40:26,  2.29s/it]
ChatCompletion(id='chatcmpl-9MzepOyTV8gyq83jeNfWCdtJEz3wm', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["American Express issue", "Apple Pay problem", "card top-up error"]', role='assistant', function_call=None, tool_calls=None))], created=1715267255, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=237, total_tokens=253))
["American Express issue", "Apple Pay problem", "card top-up error"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My top up is not working in Apple Pay."

Keyphrases:
2980it [1:40:28,  1.95s/it]
ChatCompletion(id='chatcmpl-9Mzer5mjTkLHAwUJzG9NQLHkDMM2O', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "Apple Pay not working", "payment method issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715267257, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["top up issue", "Apple Pay not working", "payment method issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is Apple Pay a possible top up option?"

Keyphrases:
2981it [1:40:29,  1.82s/it]
ChatCompletion(id='chatcmpl-9MzesVURWPHMjOfqbGZTiMHNVJZiZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Apple Pay", "top-up options", "payment methods"]', role='assistant', function_call=None, tool_calls=None))], created=1715267258, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["Apple Pay", "top-up options", "payment methods"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't know how to top up my Google pay."

Keyphrases:
2982it [1:40:31,  1.85s/it]
ChatCompletion(id='chatcmpl-9MzeuF5NtrqxN2PCUIxIVDReKGzCK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Google Pay top up", "add money to Google Pay", "funding Google Pay"]', role='assistant', function_call=None, tool_calls=None))], created=1715267260, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=19, prompt_tokens=230, total_tokens=249))
["Google Pay top up", "add money to Google Pay", "funding Google Pay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I top up from my Apple Watch?"

Keyphrases:
2983it [1:40:32,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzevtglixYrzkh0j5v5vMi5xnUbG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["mobile top up", "top up via wearable", "wearable banking"]', role='assistant', function_call=None, tool_calls=None))], created=1715267261, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=227, total_tokens=243))
["mobile top up", "top up via wearable", "wearable banking"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use my American Express stored in Apple Pay to top up?"

Keyphrases:
2984it [1:40:34,  1.79s/it]
ChatCompletion(id='chatcmpl-9MzexSsxMMB7J17xNOJaCAITSEru6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["use stored card", "top up with Apple Pay", "American Express top up"]', role='assistant', function_call=None, tool_calls=None))], created=1715267263, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=232, total_tokens=250))
["use stored card", "top up with Apple Pay", "American Express top up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "is apple pay costly?"

Keyphrases:
2985it [1:40:37,  1.94s/it]
ChatCompletion(id='chatcmpl-9Mzez1K6OwViWuVFvy52eNNf46Hwd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["apple pay fees", "cost of apple pay", "payment method charges"]', role='assistant', function_call=None, tool_calls=None))], created=1715267265, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=223, total_tokens=239))
["apple pay fees", "cost of apple pay", "payment method charges"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I top up with Google Pay?"

Keyphrases:
2986it [1:40:39,  1.96s/it]
ChatCompletion(id='chatcmpl-9Mzf11b8HqY50cDmwt6wGhKs7utKI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up mobile", "Google Pay top up", "add funds with Google Pay"]', role='assistant', function_call=None, tool_calls=None))], created=1715267267, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=227, total_tokens=245))
["top up mobile", "Google Pay top up", "add funds with Google Pay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I can't top up my account using my American Express with Apple Pay."

Keyphrases:
2987it [1:40:40,  1.84s/it]
ChatCompletion(id='chatcmpl-9Mzf3RzxopZIqZiw7NM5ynOiph1ck', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issues", "American Express compatibility", "Apple Pay issues"]', role='assistant', function_call=None, tool_calls=None))], created=1715267269, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["top up issues", "American Express compatibility", "Apple Pay issues"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got my American Express in Apple Pay, why is top up not working?"

Keyphrases:
2988it [1:40:42,  1.81s/it]
ChatCompletion(id='chatcmpl-9Mzf4rWqTY8wFAi27GLfvZ4MXI7eo', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Apple Pay issue", "top up failure", "digital wallet top up problem"]', role='assistant', function_call=None, tool_calls=None))], created=1715267270, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=234, total_tokens=251))
["Apple Pay issue", "top up failure", "digital wallet top up problem"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got my American Express in Apple Bay but top up is not working"

Keyphrases:
2989it [1:40:44,  1.88s/it]
ChatCompletion(id='chatcmpl-9Mzf6Y2SXe1lZtCgipXzOz2zW0NQE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issues", "American Express top up", "payment not processing"]', role='assistant', function_call=None, tool_calls=None))], created=1715267272, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=233, total_tokens=249))
["top up issues", "American Express top up", "payment not processing"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I top up? Can I use my apple watch?"

Keyphrases:
2990it [1:40:46,  1.99s/it]
ChatCompletion(id='chatcmpl-9Mzf8nJE07d72UdjIYq85SqhuwPA1', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up account", "account reloading", "using wearable devices", "apple watch payments"]', role='assistant', function_call=None, tool_calls=None))], created=1715267274, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=19, prompt_tokens=231, total_tokens=250))
["top up account", "account reloading", "using wearable devices", "apple watch payments"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to use Apple Pay to put money in my account?"

Keyphrases:
2991it [1:40:50,  2.53s/it]
ChatCompletion(id='chatcmpl-9MzfAyS8I0hyXeuwUxA97sLeA4Xne', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Apple Pay deposit", "mobile payment funding", "deposit using Apple Pay"]', role='assistant', function_call=None, tool_calls=None))], created=1715267276, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=232, total_tokens=248))
["Apple Pay deposit", "mobile payment funding", "deposit using Apple Pay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "My American Express is in my Apple Pay and the top up is failing, why?"

Keyphrases:
2992it [1:40:51,  2.17s/it]
ChatCompletion(id='chatcmpl-9MzfEv1uIIaWdWDtuZwzHPDFkB5Zx', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Apple Pay top up issue", "American Express top up failure", "payment method issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715267280, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=19, prompt_tokens=235, total_tokens=254))
["Apple Pay top up issue", "American Express top up failure", "payment method issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I top-ff my account using my Apple Watch?"

Keyphrases:
2993it [1:40:53,  2.12s/it]
ChatCompletion(id='chatcmpl-9MzfGLM6I1joXb9aaJG4ZKMgC8NyH', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top-up methods", "wearable banking", "Apple Watch banking"]', role='assistant', function_call=None, tool_calls=None))], created=1715267282, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=231, total_tokens=246))
["top-up methods", "wearable banking", "Apple Watch banking"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "can google pay be used to make a top-up"

Keyphrases:
2994it [1:40:57,  2.63s/it]
ChatCompletion(id='chatcmpl-9MzfIbX0EiORhkfkHg0Q6Mc2NNrXG', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Google Pay usage", "mobile top-up", "Google Pay top-up"]', role='assistant', function_call=None, tool_calls=None))], created=1715267284, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=229, total_tokens=245))
["Google Pay usage", "mobile top-up", "Google Pay top-up"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I get the Top Up feature on my apple watch working?"

Keyphrases:
2995it [1:40:59,  2.31s/it]
ChatCompletion(id='chatcmpl-9MzfLyK865RPq7AB6IykpTpHPWcvK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up activation", "apple watch banking", "enable feature"]', role='assistant', function_call=None, tool_calls=None))], created=1715267287, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=232, total_tokens=246))
["top up activation", "apple watch banking", "enable feature"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I troubleshoot Google pay top up?"

Keyphrases:
2996it [1:41:01,  2.20s/it]
ChatCompletion(id='chatcmpl-9MzfNeqXunIeL3sUKqTlPf1lJvuHv', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Google Pay issues", "troubleshooting top up", "payment failure"]', role='assistant', function_call=None, tool_calls=None))], created=1715267289, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["Google Pay issues", "troubleshooting top up", "payment failure"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I top up with Apple Pay?"

Keyphrases:
2997it [1:41:03,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzfPkSE1YDuMNJYEXntZTvNxAR9i', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up", "Apple Pay", "add funds with Apple Pay"]', role='assistant', function_call=None, tool_calls=None))], created=1715267291, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["top up", "Apple Pay", "add funds with Apple Pay"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Why isn't my top up working using my saved American Express in ApplePay?"

Keyphrases:
2998it [1:41:06,  2.49s/it]
ChatCompletion(id='chatcmpl-9MzfR4cwnjWCHgBcc2tGNl4DStOGZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["top up issue", "ApplePay problem", "American Express not working"]', role='assistant', function_call=None, tool_calls=None))], created=1715267293, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=234, total_tokens=250))
["top up issue", "ApplePay problem", "American Express not working"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I use the top up app with my apple watch?"

Keyphrases:
2999it [1:41:12,  3.40s/it]
ChatCompletion(id='chatcmpl-9MzfUH45561m1LY0si9crj5ufzNLd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["app compatibility", "using app on apple watch", "top up via wearable"]', role='assistant', function_call=None, tool_calls=None))], created=1715267296, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["app compatibility", "using app on apple watch", "top up via wearable"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Google pay and top up, I want it, can I get it?"

Keyphrases:
3000it [1:41:14,  3.00s/it]
ChatCompletion(id='chatcmpl-9Mzfa3US2ABd5VxQiLkW66Jm055gD', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["Google Pay", "account top-up", "mobile payment setup"]', role='assistant', function_call=None, tool_calls=None))], created=1715267302, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["Google Pay", "account top-up", "mobile payment setup"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What can I use to verify my identify?"

Keyphrases:
3001it [1:41:16,  2.81s/it]
ChatCompletion(id='chatcmpl-9Mzfd53iO81RY8WmuJEvuyNK2uAoP', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification methods", "account verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715267305, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["identity verification", "verification methods", "account verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do you need to verify my identity?"

Keyphrases:
3002it [1:41:17,  2.42s/it]
ChatCompletion(id='chatcmpl-9Mzfe3n2eTXQLaty0WrCeP82vRDZj', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification requirements", "verification process", "account security verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715267306, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["identity verification requirements", "verification process", "account security verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to verify my identity, but how do I do that?"

Keyphrases:
3003it [1:41:19,  2.06s/it]
ChatCompletion(id='chatcmpl-9Mzfg7Ae59k9kc2AViBTB0TV1RtNR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verify identity", "account verification process"]', role='assistant', function_call=None, tool_calls=None))], created=1715267308, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=232, total_tokens=245))
["identity verification", "verify identity", "account verification process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How can I verify my indentity?"

Keyphrases:
3004it [1:41:20,  1.87s/it]
ChatCompletion(id='chatcmpl-9MzfhVwzoG2LkblKGIaow3hIo8Yb0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verify identity", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715267309, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["identity verification", "verify identity", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What is needed to prove my identity?"

Keyphrases:
3005it [1:41:21,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzfirhdbfIdjiUJpWfpZIJgxTadY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification requirements", "proof of identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715267310, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["identity verification", "verification requirements", "proof of identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do you need for my identity check?"

Keyphrases:
3006it [1:41:22,  1.52s/it]
ChatCompletion(id='chatcmpl-9MzfkJIQzJtFJrTDqr2XLWZpDUAZc', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "documentation for verification", "KYC requirements"]', role='assistant', function_call=None, tool_calls=None))], created=1715267312, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=227, total_tokens=241))
["identity verification", "documentation for verification", "KYC requirements"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do you verify an identity?"

Keyphrases:
3007it [1:41:24,  1.55s/it]
ChatCompletion(id='chatcmpl-9MzflMIxvJuqpGMH2wMexmvRXVjrL', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verify identity", "KYC process"]', role='assistant', function_call=None, tool_calls=None))], created=1715267313, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["identity verification", "verify identity", "KYC process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there a specific type you need for identity verification?"

Keyphrases:
3008it [1:41:26,  1.61s/it]
ChatCompletion(id='chatcmpl-9MzfmdxdvOeCPG3iOeNmVtTY2Wvia', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification requirements", "ID type"]', role='assistant', function_call=None, tool_calls=None))], created=1715267314, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["identity verification", "verification requirements", "ID type"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I got a message that I need to verify my identity; what do I do?"

Keyphrases:
3009it [1:41:28,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzfoYMsXbU0tX2UZCVP8iverVjAk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "account security", "verify identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715267316, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=235, total_tokens=247))
["identity verification", "account security", "verify identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are there any documents needed for the identity check?"

Keyphrases:
3010it [1:41:29,  1.62s/it]
ChatCompletion(id='chatcmpl-9MzfqBvyPU9UYdY4tZb4rGJLIIMqr', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "required documents", "KYC documentation"]', role='assistant', function_call=None, tool_calls=None))], created=1715267318, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["identity verification", "required documents", "KYC documentation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the steps I need to take to verify my identity?"

Keyphrases:
3011it [1:41:31,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzfrsJ2Xr42NYDmk5b37hsBag1du', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verify identity", "account verification process"]', role='assistant', function_call=None, tool_calls=None))], created=1715267319, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["identity verification", "verify identity", "account verification process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I need to verify my identity"

Keyphrases:
3012it [1:41:33,  1.77s/it]
ChatCompletion(id='chatcmpl-9Mzfuz2K7mW1udvwP4IE2TzdSKjGk', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification requirements", "KYC documents"]', role='assistant', function_call=None, tool_calls=None))], created=1715267322, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "verification requirements", "KYC documents"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need to verify my identity"

Keyphrases:
3013it [1:41:34,  1.63s/it]
ChatCompletion(id='chatcmpl-9Mzfv8Wzj1cvtvGV55vYQujYQp2ZS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "account verification", "verify identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715267323, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["identity verification", "account verification", "verify identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need some help with identity verification."

Keyphrases:
3014it [1:41:36,  1.73s/it]
ChatCompletion(id='chatcmpl-9MzfxClpARKKMT0fDSv4i4Hblbs6C', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification assistance", "verification help", "ID verification issue"]', role='assistant', function_call=None, tool_calls=None))], created=1715267325, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["identity verification assistance", "verification help", "ID verification issue"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What's the process for ID verification?"

Keyphrases:
3015it [1:41:38,  1.63s/it]
ChatCompletion(id='chatcmpl-9MzfzuiS3AQSUG5dtuYw12UHi5x5N', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification process", "identity confirmation", "verification steps"]', role='assistant', function_call=None, tool_calls=None))], created=1715267327, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["ID verification process", "identity confirmation", "verification steps"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to know how I can verify my Identity."

Keyphrases:
3016it [1:41:40,  1.86s/it]
ChatCompletion(id='chatcmpl-9Mzg0HsTLXxKEXKOBYaUbx0gCMSBB', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verify identity", "account verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715267328, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=12, prompt_tokens=230, total_tokens=242))
["identity verification", "verify identity", "account verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What kind of documents do I need for the identity check?"

Keyphrases:
3017it [1:41:42,  1.91s/it]
ChatCompletion(id='chatcmpl-9Mzg2ohFwneblDDMMZVTk4FPMlzGe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "required documents", "KYC documents"]', role='assistant', function_call=None, tool_calls=None))], created=1715267330, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["identity verification", "required documents", "KYC documents"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Let me know the steps for the identity checks"

Keyphrases:
3018it [1:41:44,  1.99s/it]
ChatCompletion(id='chatcmpl-9Mzg4Cs5ETugZNttOZZrorc7AD5ZR', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification steps", "KYC process"]', role='assistant', function_call=None, tool_calls=None))], created=1715267332, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["identity verification", "verification steps", "KYC process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What should I do to verify my identity?"

Keyphrases:
3019it [1:41:46,  1.85s/it]
ChatCompletion(id='chatcmpl-9Mzg7t0pLwkPFeL7Pc2RM1hZKTA9p', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verify identity", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715267335, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["identity verification", "verify identity", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the steps to verify my identity?"

Keyphrases:
3020it [1:41:49,  2.19s/it]
ChatCompletion(id='chatcmpl-9Mzg9DmHt6f5ICEdYR6DOzd92jzeF', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verify identity", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715267337, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["identity verification", "verify identity", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How does my identity get verified?"

Keyphrases:
3021it [1:41:50,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzgBAuWZfkv9HrrVdGSV0w9tn1vJ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification process", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715267339, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["identity verification", "verification process", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What things do I need to verify my identity?"

Keyphrases:
3022it [1:41:52,  1.88s/it]
ChatCompletion(id='chatcmpl-9MzgDATPq8hkHdnuwnF4XlIOARCgS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC requirements", "verification documents"]', role='assistant', function_call=None, tool_calls=None))], created=1715267341, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["identity verification", "KYC requirements", "verification documents"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What steps do I take to verify my identity?"

Keyphrases:
3023it [1:41:54,  1.93s/it]
ChatCompletion(id='chatcmpl-9MzgEHCNNId7Dms7eegXx3DX26Lhz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verify identity", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715267342, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["identity verification", "verify identity", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I verify my identity online?"

Keyphrases:
3024it [1:41:55,  1.78s/it]
ChatCompletion(id='chatcmpl-9MzgGfeirHsyJV3hRnHIlYmFiavPa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "online verification", "verify identity online"]', role='assistant', function_call=None, tool_calls=None))], created=1715267344, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["identity verification", "online verification", "verify identity online"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "do the details of my profile have to match my documents"

Keyphrases:
3025it [1:41:57,  1.65s/it]
ChatCompletion(id='chatcmpl-9MzgIyehHcYJhTCJ2ysMrFCjMAF5U', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["profile verification", "account details match", "document consistency"]', role='assistant', function_call=None, tool_calls=None))], created=1715267346, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["profile verification", "account details match", "document consistency"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I verify my identity?"

Keyphrases:
3026it [1:41:59,  1.90s/it]
ChatCompletion(id='chatcmpl-9MzgJ2esbCc6kM9iWJz1UbhYclpRK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verify identity", "account security"]', role='assistant', function_call=None, tool_calls=None))], created=1715267347, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["identity verification", "verify identity", "account security"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "When getting my ID checked, what are the steps involved?"

Keyphrases:
3027it [1:42:01,  1.75s/it]
ChatCompletion(id='chatcmpl-9MzgL6qIN292IqVErQIJ8fhGnlM1G', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["ID verification process", "steps for identity check", "verification steps"]', role='assistant', function_call=None, tool_calls=None))], created=1715267349, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=15, prompt_tokens=230, total_tokens=245))
["ID verification process", "steps for identity check", "verification steps"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "do I need anything for the identity check?"

Keyphrases:
3028it [1:42:04,  2.15s/it]
ChatCompletion(id='chatcmpl-9MzgNIqpvRSD5XyDjVECeUXjTvCQp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "ID check requirements", "verification process"]', role='assistant', function_call=None, tool_calls=None))], created=1715267351, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "ID check requirements", "verification process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "which kind of documentation do I need for identity check?"

Keyphrases:
3029it [1:42:05,  2.03s/it]
ChatCompletion(id='chatcmpl-9MzgQndyyEOdilpwoEEAatHRThQ3h', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "documentation required", "KYC documents"]', role='assistant', function_call=None, tool_calls=None))], created=1715267354, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["identity verification", "documentation required", "KYC documents"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How do I go forth on verifying my identity?"

Keyphrases:
3030it [1:42:07,  1.85s/it]
ChatCompletion(id='chatcmpl-9MzgSqUGQCCXfrqgFk4sx75eZrcL8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verify identity", "account verification process"]', role='assistant', function_call=None, tool_calls=None))], created=1715267356, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["identity verification", "verify identity", "account verification process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What can I do to verify my identity?"

Keyphrases:
3031it [1:42:10,  2.12s/it]
ChatCompletion(id='chatcmpl-9MzgTWq6CnDulYMPuAbvrM5OVXRCI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verify identity", "account security verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715267357, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "verify identity", "account security verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do you need so I can verify my identity?"

Keyphrases:
3032it [1:42:14,  2.85s/it]
ChatCompletion(id='chatcmpl-9MzgWVsj6lThiwTP6YfMhEqqjpSnp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "verification requirements", "account verification"]', role='assistant', function_call=None, tool_calls=None))], created=1715267360, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=229, total_tokens=241))
["identity verification", "verification requirements", "account verification"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I need to show who I am?"

Keyphrases:
3033it [1:42:16,  2.40s/it]
ChatCompletion(id='chatcmpl-9MzgaYzrNOmfrkgqPhzdD4Wq9eZvu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "KYC requirements", "proof of identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715267364, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=14, prompt_tokens=228, total_tokens=242))
["identity verification", "KYC requirements", "proof of identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do I need any kind of documentation for the identity check?"

Keyphrases:
3034it [1:42:19,  2.68s/it]
ChatCompletion(id='chatcmpl-9MzgcWF8V0gJCBByaM9D4YEizeQLI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "required documents", "documentation for identity check"]', role='assistant', function_call=None, tool_calls=None))], created=1715267366, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["identity verification", "required documents", "documentation for identity check"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What will I need for identity verification?"

Keyphrases:
3035it [1:42:20,  2.33s/it]
ChatCompletion(id='chatcmpl-9MzgfQoYXdnrEnBvUDbeqke9x3Nfp', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification requirements", "verification documents", "KYC process"]', role='assistant', function_call=None, tool_calls=None))], created=1715267369, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=226, total_tokens=240))
["identity verification requirements", "verification documents", "KYC process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there any way to verify who I am?"

Keyphrases:
3036it [1:42:22,  2.03s/it]
ChatCompletion(id='chatcmpl-9Mzghhav6boyOnelQkUAUmLDUX8rY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "account security", "user authentication"]', role='assistant', function_call=None, tool_calls=None))], created=1715267371, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=228, total_tokens=240))
["identity verification", "account security", "user authentication"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is there any documentation needed for the identity check?"

Keyphrases:
3037it [1:42:23,  1.82s/it]
ChatCompletion(id='chatcmpl-9MzgisztFoZV4YUHoUklntXmuVyF0', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "documentation requirement", "KYC documents"]', role='assistant', function_call=None, tool_calls=None))], created=1715267372, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["identity verification", "documentation requirement", "KYC documents"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What all am I required to show for the identity check?"

Keyphrases:
3038it [1:42:25,  1.71s/it]
ChatCompletion(id='chatcmpl-9MzgjqKMFrZySSPau6SYatEmJd7VZ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "required documents for ID check", "ID verification process"]', role='assistant', function_call=None, tool_calls=None))], created=1715267373, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=230, total_tokens=246))
["identity verification", "required documents for ID check", "ID verification process"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I do for the identity check?"

Keyphrases:
3039it [1:42:26,  1.53s/it]
ChatCompletion(id='chatcmpl-9MzglfdEGXW9sObsFi64kgwaADAUN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "identity check process", "verify identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715267375, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=13, prompt_tokens=227, total_tokens=240))
["identity verification", "identity check process", "verify identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What do I need to do to verify my identity?"

Keyphrases:
3040it [1:42:28,  1.68s/it]
ChatCompletion(id='chatcmpl-9MzgmFZB6pU4ieH2tIb3SEDRG3UhE', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["identity verification", "account verification process", "verify identity"]', role='assistant', function_call=None, tool_calls=None))], created=1715267376, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["identity verification", "account verification process", "verify identity"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I live in the US but want to get a card"

Keyphrases:
3041it [1:42:34,  3.02s/it]
ChatCompletion(id='chatcmpl-9MzgoJti3UK99WJrNFk24qrJxsJDa', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card application US", "apply for card in US", "US card registration"]', role='assistant', function_call=None, tool_calls=None))], created=1715267378, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=17, prompt_tokens=230, total_tokens=247))
["card application US", "apply for card in US", "US card registration"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Are your cards available in Europe?"

Keyphrases:
3042it [1:42:35,  2.61s/it]
ChatCompletion(id='chatcmpl-9Mzgu3OObrlS4mbJiv1yXopkbEHXh', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card availability", "Europe availability", "geographic availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715267384, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["card availability", "Europe availability", "geographic availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I use your app if I am from the EU?"

Keyphrases:
3043it [1:42:37,  2.22s/it]
ChatCompletion(id='chatcmpl-9MzgwcmnMU6k8jvgNlAWciLYwwc3M', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["app availability", "EU support", "regional access"]', role='assistant', function_call=None, tool_calls=None))], created=1715267386, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=230, total_tokens=243))
["app availability", "EU support", "regional access"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What countries are supported?"

Keyphrases:
3044it [1:42:38,  1.99s/it]
ChatCompletion(id='chatcmpl-9Mzgx51xpXva2WCM2CFHFkqChkba6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported countries", "country availability", "service locations"]', role='assistant', function_call=None, tool_calls=None))], created=1715267387, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["supported countries", "country availability", "service locations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "i live in the US can i still get a card?"

Keyphrases:
3045it [1:42:40,  1.88s/it]
ChatCompletion(id='chatcmpl-9Mzgz2U1KHLThY1Vtgs103zS6IQw7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card eligibility", "US card availability", "international card services"]', role='assistant', function_call=None, tool_calls=None))], created=1715267389, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=230, total_tokens=244))
["card eligibility", "US card availability", "international card services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get a card outside the UK?"

Keyphrases:
3046it [1:42:42,  1.81s/it]
ChatCompletion(id='chatcmpl-9Mzh0Dwym4DaT556cAYM3JH93WBzY', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international card availability", "card issuance abroad", "card services international"]', role='assistant', function_call=None, tool_calls=None))], created=1715267390, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=15, prompt_tokens=227, total_tokens=242))
["international card availability", "card issuance abroad", "card services international"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm not in the UK, can I still get a card?"

Keyphrases:
3047it [1:42:49,  3.39s/it]
ChatCompletion(id='chatcmpl-9Mzh2fKLbaAPRgdGT49pFFFfKu6Sd', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international card eligibility", "card availability abroad", "non-UK resident card services"]', role='assistant', function_call=None, tool_calls=None))], created=1715267392, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=18, prompt_tokens=232, total_tokens=250))
["international card eligibility", "card availability abroad", "non-UK resident card services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm not in the UK, is it possible for me to still get a card?"

Keyphrases:
3048it [1:42:50,  2.83s/it]
ChatCompletion(id='chatcmpl-9Mzh9Maa95SNDreLkPsh4coHjeypO', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international card delivery", "card availability abroad", "non-UK card request"]', role='assistant', function_call=None, tool_calls=None))], created=1715267399, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=236, total_tokens=253))
["international card delivery", "card availability abroad", "non-UK card request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Now that I live in the US how can I get a card?"

Keyphrases:
3049it [1:42:54,  3.00s/it]
ChatCompletion(id='chatcmpl-9MzhAdhg0oEDIMt2AYetuuK1P0HiS', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card application US", "obtain card in US", "US banking service"]', role='assistant', function_call=None, tool_calls=None))], created=1715267400, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=232, total_tokens=249))
["card application US", "obtain card in US", "US banking service"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get one of your cards in the EU"

Keyphrases:
3050it [1:42:56,  2.87s/it]
ChatCompletion(id='chatcmpl-9MzhEe7O2CyXyoZMj55gCoinx0WCb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card availability", "EU card request", "obtaining card in EU"]', role='assistant', function_call=None, tool_calls=None))], created=1715267404, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=229, total_tokens=246))
["card availability", "EU card request", "obtaining card in EU"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get a card despite the fact I'm not in the UK?"

Keyphrases:
3051it [1:42:58,  2.47s/it]
ChatCompletion(id='chatcmpl-9MzhGbWXxIL9XzFnbeRQM9RqjvT6d', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international card eligibility", "non-resident banking services", "card availability abroad"]', role='assistant', function_call=None, tool_calls=None))], created=1715267406, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=233, total_tokens=250))
["international card eligibility", "non-resident banking services", "card availability abroad"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do I need to live to get support?"

Keyphrases:
3052it [1:43:00,  2.31s/it]
ChatCompletion(id='chatcmpl-9MzhIPsXD9bjmVTzoQ9JOkCLSK8X2', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["support eligibility", "residence requirements", "service area"]', role='assistant', function_call=None, tool_calls=None))], created=1715267408, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["support eligibility", "residence requirements", "service area"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you support the EU?"

Keyphrases:
3053it [1:43:02,  2.31s/it]
ChatCompletion(id='chatcmpl-9MzhK6CEcrJmK4qdNrc0FcJDBGC8a', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["support coverage", "EU support", "service availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715267410, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["support coverage", "EU support", "service availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "how do i get a card if i am in the usa"

Keyphrases:
3054it [1:43:03,  2.03s/it]
ChatCompletion(id='chatcmpl-9MzhM1aNPlMmeQoH0X6UgilNdKjyC', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card application", "apply for card", "USA card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715267412, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=231, total_tokens=245))
["card application", "apply for card", "USA card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Please help me get a new card, I reside in the United States."

Keyphrases:
3055it [1:43:05,  2.01s/it]
ChatCompletion(id='chatcmpl-9MzhNUifIv1Svvw4CI4aLgDKE7HWe', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["new card request", "card replacement", "issue new card"]', role='assistant', function_call=None, tool_calls=None))], created=1715267413, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=233, total_tokens=247))
["new card request", "card replacement", "issue new card"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is it possible to get a card if I'm not in the UK?"

Keyphrases:
3056it [1:43:07,  2.08s/it]
ChatCompletion(id='chatcmpl-9MzhPOvVF5nx1L1AgDJZ7WpBZasUz', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international card issuance", "card eligibility non-resident", "card availability abroad"]', role='assistant', function_call=None, tool_calls=None))], created=1715267415, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=233, total_tokens=250))
["international card issuance", "card eligibility non-resident", "card availability abroad"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Is my country supported"

Keyphrases:
3057it [1:43:09,  1.85s/it]
ChatCompletion(id='chatcmpl-9MzhShrb4Wi1WRFeWFkNLsFFnLjzu', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported countries", "country availability", "service availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715267418, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=223, total_tokens=235))
["supported countries", "country availability", "service availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "From what countries can I use this product?"

Keyphrases:
3058it [1:43:10,  1.76s/it]
ChatCompletion(id='chatcmpl-9MzhTfiognH69MLyw4KWBidNsaukQ', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["product availability", "international usage", "supported countries"]', role='assistant', function_call=None, tool_calls=None))], created=1715267419, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["product availability", "international usage", "supported countries"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where can I find your locations?"

Keyphrases:
3059it [1:43:12,  1.60s/it]
ChatCompletion(id='chatcmpl-9MzhVQJUId6vQ6rFW8TC7SjJQqt3d', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["branch locations", "ATM locations", "bank locations"]', role='assistant', function_call=None, tool_calls=None))], created=1715267421, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["branch locations", "ATM locations", "bank locations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can I get a card even if I live outside the UK?"

Keyphrases:
3060it [1:43:14,  1.86s/it]
ChatCompletion(id='chatcmpl-9MzhWgtDG7XjZFpkFT9FK0w0T4yz7', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international card eligibility", "card availability", "outside UK"]', role='assistant', function_call=None, tool_calls=None))], created=1715267422, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=231, total_tokens=244))
["international card eligibility", "card availability", "outside UK"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I am from the EU, can I sign up?"

Keyphrases:
3061it [1:43:17,  2.07s/it]
ChatCompletion(id='chatcmpl-9MzhYseN7UmwXWUCgTB8BoPlWfuJU', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["EU registration", "sign up eligibility", "international account creation"]', role='assistant', function_call=None, tool_calls=None))], created=1715267424, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=14, prompt_tokens=229, total_tokens=243))
["EU registration", "sign up eligibility", "international account creation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I would like to receive and use the card in Europe, is that possible?"

Keyphrases:
3062it [1:43:18,  1.94s/it]
ChatCompletion(id='chatcmpl-9MzhbqISTJNFhvYhB5VQPTVMfeMwI', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card usage in Europe", "international card usage", "using card abroad"]', role='assistant', function_call=None, tool_calls=None))], created=1715267427, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=16, prompt_tokens=234, total_tokens=250))
["card usage in Europe", "international card usage", "using card abroad"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What countries do you support?"

Keyphrases:
3063it [1:43:22,  2.41s/it]
ChatCompletion(id='chatcmpl-9MzhcZiDDVQ8SfROmQcESOlQhcQna', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported countries", "international support", "country availability"]', role='assistant', function_call=None, tool_calls=None))], created=1715267428, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_83397040e9', usage=CompletionUsage(completion_tokens=12, prompt_tokens=224, total_tokens=236))
["supported countries", "international support", "country availability"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What countries are you currently in?"

Keyphrases:
3064it [1:43:23,  2.14s/it]
ChatCompletion(id='chatcmpl-9Mzhg2oOpAI74GQfhF5WeOdgkbIXi', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["service locations", "countries of operation", "available countries"]', role='assistant', function_call=None, tool_calls=None))], created=1715267432, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=225, total_tokens=238))
["service locations", "countries of operation", "available countries"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What locations are you in?"

Keyphrases:
3065it [1:43:25,  2.08s/it]
ChatCompletion(id='chatcmpl-9MzhhkiKS3qFrQUlWeEGm50ZVa7D6', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["branch locations", "ATM locations", "bank locations"]', role='assistant', function_call=None, tool_calls=None))], created=1715267433, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=224, total_tokens=237))
["branch locations", "ATM locations", "bank locations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can you tell me what countries you operate in?"

Keyphrases:
3066it [1:43:27,  2.06s/it]
ChatCompletion(id='chatcmpl-9MzhjIpG7eWT2rx5duVeoZ8K6ff3r', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["operational countries", "bank presence", "service locations"]', role='assistant', function_call=None, tool_calls=None))], created=1715267435, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["operational countries", "bank presence", "service locations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I need a card, but I'm in the US at the moment."

Keyphrases:
3067it [1:43:30,  2.40s/it]
ChatCompletion(id='chatcmpl-9MzhlPGVvP1KXqX0Gcc4XCpf3vhZb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card application abroad", "US card issue", "card issuance overseas"]', role='assistant', function_call=None, tool_calls=None))], created=1715267437, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_46a93fa712', usage=CompletionUsage(completion_tokens=15, prompt_tokens=233, total_tokens=248))
["card application abroad", "US card issue", "card issuance overseas"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What countries will my card be supported in?"

Keyphrases:
3068it [1:43:32,  2.08s/it]
ChatCompletion(id='chatcmpl-9MzhpHRshBvJKWHkWlYTXPiS4USz3', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card support", "supported countries", "international use"]', role='assistant', function_call=None, tool_calls=None))], created=1715267441, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["card support", "supported countries", "international use"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Do you have a list of countries you operate in?"

Keyphrases:
3069it [1:43:34,  2.04s/it]
ChatCompletion(id='chatcmpl-9MzhqnP4COJFEAeKWm8BLhJMJHry8', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["operational countries", "service locations", "countries list"]', role='assistant', function_call=None, tool_calls=None))], created=1715267442, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=229, total_tokens=242))
["operational countries", "service locations", "countries list"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "In what countries do you do business?"

Keyphrases:
3070it [1:43:36,  2.23s/it]
ChatCompletion(id='chatcmpl-9Mzhs9FYHjE7wlgMF5xBDrgpwyE9B', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international operations", "bank locations", "countries of operation"]', role='assistant', function_call=None, tool_calls=None))], created=1715267444, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["international operations", "bank locations", "countries of operation"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I don't live in the UK.  Can I still get a card?"

Keyphrases:
3071it [1:43:39,  2.33s/it]
ChatCompletion(id='chatcmpl-9MzhvloKGbeJTy4IEN2tgvpoRP6Ca', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international card eligibility", "card availability", "non-resident banking services"]', role='assistant', function_call=None, tool_calls=None))], created=1715267447, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=234, total_tokens=250))
["international card eligibility", "card availability", "non-resident banking services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Where do you support?"

Keyphrases:
3072it [1:43:40,  2.09s/it]
ChatCompletion(id='chatcmpl-9Mzhxc7QVY8rND633x7z7vNwNPido', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported countries", "service availability", "banking regions"]', role='assistant', function_call=None, tool_calls=None))], created=1715267449, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=223, total_tokens=236))
["supported countries", "service availability", "banking regions"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Am I able to get a card in EU?"

Keyphrases:
3073it [1:43:42,  1.83s/it]
ChatCompletion(id='chatcmpl-9MzhzV68pejWu49euzd3uvTbAvU26', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card availability", "EU banking services", "obtain card in EU"]', role='assistant', function_call=None, tool_calls=None))], created=1715267451, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=16, prompt_tokens=228, total_tokens=244))
["card availability", "EU banking services", "obtain card in EU"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What countries do you currently do business in?"

Keyphrases:
3074it [1:43:43,  1.65s/it]
ChatCompletion(id='chatcmpl-9Mzi0GmpnyvqczVpUoulCN6rioZzK', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international presence", "countries served", "global operations"]', role='assistant', function_call=None, tool_calls=None))], created=1715267452, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=227, total_tokens=239))
["international presence", "countries served", "global operations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "I'm not in the UK, can I get a card?"

Keyphrases:
3075it [1:43:45,  1.80s/it]
ChatCompletion(id='chatcmpl-9Mzi1OrJfcujfEL3WvQlH6npGBotb', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international card services", "card availability abroad", "overseas card issuance"]', role='assistant', function_call=None, tool_calls=None))], created=1715267453, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_294de9593d', usage=CompletionUsage(completion_tokens=17, prompt_tokens=231, total_tokens=248))
["international card services", "card availability abroad", "overseas card issuance"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "If i'm not in the UK, can I still get a card?"

Keyphrases:
3076it [1:43:48,  2.03s/it]
ChatCompletion(id='chatcmpl-9Mzi3sLDzj44YzNwEsSbBFQAepeVs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["international card eligibility", "card availability abroad", "non-UK card request"]', role='assistant', function_call=None, tool_calls=None))], created=1715267455, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=17, prompt_tokens=233, total_tokens=250))
["international card eligibility", "card availability abroad", "non-UK card request"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "How many countries do you support?"

Keyphrases:
3077it [1:43:49,  1.97s/it]
ChatCompletion(id='chatcmpl-9Mzi6nEYfDDCrCSRFrvg450T2MsRs', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["supported countries", "international support", "global coverage"]', role='assistant', function_call=None, tool_calls=None))], created=1715267458, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=12, prompt_tokens=225, total_tokens=237))
["supported countries", "international support", "global coverage"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What countries do you do business in?"

Keyphrases:
3078it [1:43:51,  1.72s/it]
ChatCompletion(id='chatcmpl-9Mzi8Bdo4OOqtGfVxUveeQwM1qnvN', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["service availability", "countries covered", "international services"]', role='assistant', function_call=None, tool_calls=None))], created=1715267460, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_01b1fd00dd', usage=CompletionUsage(completion_tokens=12, prompt_tokens=226, total_tokens=238))
["service availability", "countries covered", "international services"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "What are the countries you operate in."

Keyphrases:
3079it [1:43:52,  1.69s/it]
ChatCompletion(id='chatcmpl-9Mzi9fkKRE2lYSKe7mq30ucf5eKHX', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["operating countries", "bank presence", "service locations"]', role='assistant', function_call=None, tool_calls=None))], created=1715267461, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=226, total_tokens=239))
["operating countries", "bank presence", "service locations"]
PROMPT:
I am trying to cluster queries for a online banking system based on whether they express the same general user intent. To help me with this, for a given banking query, provide a comprehensive set of keyphrases that could describe this query's intent. These keyphrases should be distinct from those that might describe banking-related queries with different intents. Generate the set of keyphrases as a JSON-formatted list without writing ```json
 in the response, the response must be in this format : ["x", "y", "z"].

Query: "How do I locate my card?"

Keyphrases: ["card status", "status update", "card location"]

Query: "Whats the delivery time to the United States?"

Keyphrases: ["delivery time", "ETA", "card delivery"]

Query: "Can you cancel my purchase?"

Keyphrases: ["cancel purchase", "refund"]

Query: "Why don't I have my transfer?"

Keyphrases: ["transfer", "transfer failed"]

Query: "Can the card be mailed and used in Europe?"

Keyphrases:
3080it [1:43:54,  2.02s/it]
ChatCompletion(id='chatcmpl-9MziASqctEiUxkUA9ikhrPTAgtPok', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='["card usage", "international use", "Europe card mailing"]', role='assistant', function_call=None, tool_calls=None))], created=1715267462, model='gpt-4-turbo-2024-04-09', object='chat.completion', system_fingerprint='fp_ea6eb70039', usage=CompletionUsage(completion_tokens=13, prompt_tokens=228, total_tokens=241))
["card usage", "international use", "Europe card mailing"]
load INSTRUCTOR_Transformer

max_seq_length  512
100%|████████████████████████████████████████████████████████████████| 76/76 [00:01<00:00, 73.46it/s]
Total K-Means++ times: {'Initial Euclidean Distances': 0.023078205005731434, 'Pairwise Euclidean Distances': 0.9422135529603111, 'Compute candidate potentials': 0.005042911026976071, 'Total K-Means++ time': 1.0593530439946335}
iteration 0
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.001 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 0 took 1.162 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.069}
iteration 1
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 1 took 1.19 seconds.
Timer dict: {'Centroid normalization': 0.004, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 2
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 2 took 1.216 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 3
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 3 took 1.242 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 4
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.006 seconds.
K-Means iteration 4 took 1.272 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.006, 'Check convergence': 0.001}
iteration 5
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 5 took 1.3 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 6
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 6 took 1.327 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 7
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 7 took 1.353 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 8
Assigning points to clusters took 0.033 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 8 took 1.393 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.033, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 9
Assigning points to clusters took 0.049 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 9 took 1.448 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.049, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 10
Assigning points to clusters took 0.033 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 10 took 1.487 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.033, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 11
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 11 took 1.513 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 12
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 12 took 1.541 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 13
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 13 took 1.569 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 14
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 14 took 1.597 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 15
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 15 took 1.627 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 16
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 16 took 1.658 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 17
Assigning points to clusters took 0.029 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 17 took 1.695 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.029, 'Estimate cluster centers': 0.006, 'Check convergence': 0.001}
iteration 18
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 18 took 1.726 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 19
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 19 took 1.755 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 20
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 20 took 1.785 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 21
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 21 took 1.816 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 22
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.006 seconds.
K-Means iteration 22 took 1.849 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.006, 'Check convergence': 0.001}
iteration 23
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 23 took 1.881 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 24
Assigning points to clusters took 0.029 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 24 took 1.917 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.029, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 25
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 25 took 1.948 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 26
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 26 took 1.977 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 27
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 27 took 2.005 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 28
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 28 took 2.036 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 29
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 29 took 2.065 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 30
Assigning points to clusters took 0.058 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 30 took 2.129 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.058, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 31
Assigning points to clusters took 0.048 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 31 took 2.184 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.048, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 32
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 32 took 2.214 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 33
Assigning points to clusters took 0.029 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 33 took 2.25 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.03, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 34
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 34 took 2.28 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 35
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 35 took 2.308 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 36
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 36 took 2.341 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.027, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 37
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 37 took 2.37 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 38
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 38 took 2.397 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 39
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 39 took 2.426 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 40
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 40 took 2.456 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 41
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 41 took 2.486 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 42
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 42 took 2.515 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 43
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 43 took 2.547 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 44
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 44 took 2.576 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 45
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 45 took 2.607 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 46
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 46 took 2.636 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 47
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 47 took 2.665 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 48
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 48 took 2.693 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 49
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 49 took 2.722 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 50
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 50 took 2.754 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 51
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 51 took 2.783 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 52
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 52 took 2.813 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 53
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 53 took 2.841 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 54
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 54 took 2.87 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 55
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 55 took 2.9 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 56
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 56 took 2.929 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 57
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 57 took 2.961 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 58
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 58 took 2.991 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 59
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 59 took 3.02 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 60
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 60 took 3.051 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 61
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 61 took 3.081 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 62
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 62 took 3.109 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 63
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 63 took 3.138 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 64
Assigning points to clusters took 0.032 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 64 took 3.177 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.033, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 65
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 65 took 3.203 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 66
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 66 took 3.23 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 67
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 67 took 3.257 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 68
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 68 took 3.284 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 69
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 69 took 3.31 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 70
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 70 took 3.337 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 71
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 71 took 3.364 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 72
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 72 took 3.394 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 73
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 73 took 3.421 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 74
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 74 took 3.447 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 75
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 75 took 3.474 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 76
Assigning points to clusters took 0.028 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 76 took 3.508 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.028, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 77
Assigning points to clusters took 0.038 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 77 took 3.553 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.038, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 78
Assigning points to clusters took 0.027 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 78 took 3.586 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.027, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 79
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 79 took 3.616 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 80
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 80 took 3.643 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 81
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 81 took 3.672 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 82
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 82 took 3.699 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 83
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 83 took 3.727 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 84
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 84 took 3.753 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 85
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 85 took 3.779 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 86
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 86 took 3.806 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 87
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 87 took 3.835 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 88
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 88 took 3.863 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 89
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 89 took 3.891 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 90
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 90 took 3.918 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 91
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 91 took 3.945 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 92
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 92 took 3.972 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 93
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 93 took 3.998 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 94
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 94 took 4.025 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 95
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 95 took 4.054 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 96
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.022 seconds.
K-Means iteration 96 took 4.1 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.022, 'Check convergence': 0.001}
iteration 97
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 97 took 4.129 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 98
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 98 took 4.157 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 99
Assigning points to clusters took 0.028 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 99 took 4.191 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.028, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
Took 6620.444 seconds to cluster points.


Starting experiments for 1th seed
Running GPTExpansionClustering for seed 1
3080it [00:00, 4943917.46it/s]
load INSTRUCTOR_Transformer

max_seq_length  512
100%|████████████████████████████████████████████████████████████████| 76/76 [00:01<00:00, 75.36it/s]
Total K-Means++ times: {'Initial Euclidean Distances': 0.009122512012254447, 'Pairwise Euclidean Distances': 0.918161246998352, 'Compute candidate potentials': 0.004248311015544459, 'Total K-Means++ time': 1.0195730760024162}
iteration 0
Assigning points to clusters took 0.033 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 0 took 1.061 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.033, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 1
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 1 took 1.089 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 2
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 2 took 1.117 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 3
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 3 took 1.145 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 4
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 4 took 1.173 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 5
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 5 took 1.201 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 6
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 6 took 1.229 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 7
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 7 took 1.257 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 8
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 8 took 1.285 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 9
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 9 took 1.313 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 10
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 10 took 1.34 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 11
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 11 took 1.368 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 12
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 12 took 1.397 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 13
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 13 took 1.425 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 14
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 14 took 1.453 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 15
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 15 took 1.481 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 16
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 16 took 1.509 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 17
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 17 took 1.537 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 18
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 18 took 1.564 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 19
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 19 took 1.592 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 20
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 20 took 1.62 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 21
Assigning points to clusters took 0.03 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 21 took 1.656 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.03, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 22
Assigning points to clusters took 0.032 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 22 took 1.694 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.032, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 23
Assigning points to clusters took 0.043 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 23 took 1.743 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.043, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 24
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 24 took 1.776 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 25
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 25 took 1.804 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 26
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 26 took 1.832 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 27
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 27 took 1.864 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 28
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 28 took 1.893 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 29
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 29 took 1.921 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 30
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 30 took 1.949 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 31
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 31 took 1.977 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 32
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 32 took 2.006 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 33
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 33 took 2.033 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 34
Assigning points to clusters took 0.05 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 34 took 2.091 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.051, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 35
Assigning points to clusters took 0.034 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 35 took 2.131 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.034, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 36
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 36 took 2.158 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 37
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 37 took 2.186 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 38
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 38 took 2.215 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 39
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 39 took 2.242 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 40
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 40 took 2.27 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 41
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 41 took 2.303 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 42
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 42 took 2.331 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 43
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 43 took 2.358 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 44
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 44 took 2.386 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 45
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 45 took 2.414 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 46
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 46 took 2.442 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 47
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 47 took 2.469 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 48
Assigning points to clusters took 0.029 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 48 took 2.505 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.029, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 49
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 49 took 2.537 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 50
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 50 took 2.565 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 51
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 51 took 2.592 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 52
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 52 took 2.621 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 53
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 53 took 2.65 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 54
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 54 took 2.678 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 55
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 55 took 2.707 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 56
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 56 took 2.735 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 57
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 57 took 2.763 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 58
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 58 took 2.79 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 59
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 59 took 2.819 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 60
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 60 took 2.846 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 61
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 61 took 2.874 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 62
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 62 took 2.902 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 63
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 63 took 2.932 seconds.
Timer dict: {'Centroid normalization': 0.003, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 64
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 64 took 2.959 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 65
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 65 took 2.987 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 66
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 66 took 3.015 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 67
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 67 took 3.043 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 68
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 68 took 3.071 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 69
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 69 took 3.098 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 70
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.013 seconds.
K-Means iteration 70 took 3.135 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.013, 'Check convergence': 0.001}
iteration 71
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 71 took 3.163 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 72
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 72 took 3.191 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 73
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 73 took 3.219 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 74
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 74 took 3.247 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 75
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 75 took 3.274 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 76
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 76 took 3.302 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 77
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 77 took 3.331 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 78
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 78 took 3.361 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 79
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 79 took 3.389 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 80
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 80 took 3.418 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 81
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 81 took 3.446 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 82
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 82 took 3.473 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 83
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 83 took 3.501 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 84
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 84 took 3.528 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 85
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 85 took 3.557 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 86
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 86 took 3.586 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 87
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 87 took 3.613 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 88
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 88 took 3.641 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 89
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 89 took 3.671 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 90
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 90 took 3.698 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 91
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 91 took 3.726 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 92
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 92 took 3.754 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 93
Assigning points to clusters took 0.037 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 93 took 3.798 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.038, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 94
Assigning points to clusters took 0.051 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 94 took 3.855 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.051, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 95
Assigning points to clusters took 0.032 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 95 took 3.894 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.032, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 96
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 96 took 3.922 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 97
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 97 took 3.953 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 98
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 98 took 3.981 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 99
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 99 took 4.014 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.027, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
Took 402.798 seconds to cluster points.


Starting experiments for 2th seed
Running GPTExpansionClustering for seed 2
3080it [00:00, 2477172.83it/s]
load INSTRUCTOR_Transformer

max_seq_length  512
100%|█████████████████████████████████████████████████████████████████████████| 76/76 [00:01<00:00, 75.11it/s]
Total K-Means++ times: {'Initial Euclidean Distances': 0.015024630003608763, 'Pairwise Euclidean Distances': 0.9194975899445126, 'Compute candidate potentials': 0.004412387032061815, 'Total K-Means++ time': 1.0296241360047134}
iteration 0
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 0 took 1.072 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.006}
iteration 1
Assigning points to clusters took 0.036 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 1 took 1.114 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.036, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 2
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 2 took 1.144 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 3
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 3 took 1.174 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 4
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 4 took 1.204 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 5
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 5 took 1.235 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 6
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 6 took 1.266 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 7
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 7 took 1.297 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 8
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 8 took 1.327 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 9
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 9 took 1.357 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 10
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 10 took 1.387 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 11
Assigning points to clusters took 0.033 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 11 took 1.426 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.033, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 12
Assigning points to clusters took 0.061 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 12 took 1.495 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.062, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 13
Assigning points to clusters took 0.047 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 13 took 1.549 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.048, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 14
Assigning points to clusters took 0.048 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 14 took 1.603 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.048, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 15
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 15 took 1.634 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 16
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 16 took 1.664 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 17
Assigning points to clusters took 0.047 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 17 took 1.718 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.048, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 18
Assigning points to clusters took 0.046 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 18 took 1.771 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.046, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 19
Assigning points to clusters took 0.064 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 19 took 1.842 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.065, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 20
Assigning points to clusters took 0.049 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.006 seconds.
K-Means iteration 20 took 1.899 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.049, 'Estimate cluster centers': 0.006, 'Check convergence': 0.001}
iteration 21
Assigning points to clusters took 0.038 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 21 took 1.943 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.038, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 22
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 22 took 1.971 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 23
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 23 took 1.998 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 24
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 24 took 2.026 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 25
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 25 took 2.053 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 26
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 26 took 2.081 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 27
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 27 took 2.109 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 28
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 28 took 2.136 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 29
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 29 took 2.167 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 30
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 30 took 2.195 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 31
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 31 took 2.224 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 32
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 32 took 2.251 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 33
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 33 took 2.279 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 34
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 34 took 2.307 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 35
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 35 took 2.335 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 36
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 36 took 2.363 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 37
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 37 took 2.391 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 38
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 38 took 2.419 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 39
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 39 took 2.447 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 40
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 40 took 2.475 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 41
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 41 took 2.503 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 42
Assigning points to clusters took 0.028 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 42 took 2.538 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.029, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 43
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 43 took 2.566 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 44
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 44 took 2.594 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 45
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 45 took 2.622 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 46
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 46 took 2.649 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 47
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 47 took 2.677 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 48
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 48 took 2.705 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 49
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 49 took 2.732 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 50
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 50 took 2.76 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 51
Assigning points to clusters took 0.048 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 51 took 2.815 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.048, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 52
Assigning points to clusters took 0.034 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 52 took 2.855 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.034, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 53
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 53 took 2.887 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 54
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 54 took 2.919 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 55
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 55 took 2.95 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 56
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 56 took 2.978 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 57
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 57 took 3.006 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 58
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 58 took 3.038 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 59
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 59 took 3.065 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 60
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 60 took 3.092 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 61
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 61 took 3.12 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 62
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 62 took 3.147 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 63
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 63 took 3.174 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 64
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 64 took 3.202 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 65
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 65 took 3.229 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 66
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 66 took 3.259 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 67
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 67 took 3.286 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 68
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 68 took 3.319 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 69
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 69 took 3.346 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 70
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 70 took 3.374 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 71
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 71 took 3.403 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 72
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 72 took 3.43 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 73
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 73 took 3.459 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 74
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 74 took 3.487 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 75
Assigning points to clusters took 0.035 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 75 took 3.529 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.035, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 76
Assigning points to clusters took 0.029 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 76 took 3.564 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.029, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 77
Assigning points to clusters took 0.03 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 77 took 3.601 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.03, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 78
Assigning points to clusters took 0.033 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 78 took 3.64 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.033, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 79
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 79 took 3.672 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 80
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 80 took 3.7 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 81
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 81 took 3.728 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 82
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 82 took 3.756 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 83
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 83 took 3.784 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 84
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 84 took 3.812 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 85
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 85 took 3.839 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 86
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 86 took 3.867 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 87
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 87 took 3.9 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.027, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 88
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 88 took 3.928 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 89
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 89 took 3.955 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 90
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 90 took 3.983 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 91
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 91 took 4.011 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 92
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 92 took 4.039 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 93
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 93 took 4.066 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 94
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 94 took 4.094 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 95
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 95 took 4.122 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 96
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 96 took 4.15 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 97
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 97 took 4.177 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 98
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 98 took 4.205 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 99
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 99 took 4.233 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
Took 387.421 seconds to cluster points.


Starting experiments for 3th seed
Running GPTExpansionClustering for seed 3
3080it [00:00, 4291845.95it/s]
load INSTRUCTOR_Transformer

max_seq_length  512
100%|█████████████████████████████████████████████████████████████████████████| 76/76 [00:00<00:00, 78.57it/s]
Total K-Means++ times: {'Initial Euclidean Distances': 0.010697601988795213, 'Pairwise Euclidean Distances': 0.8726882730843499, 'Compute candidate potentials': 0.004354943957878277, 'Total K-Means++ time': 0.979834261990618}
iteration 0
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 0 took 1.013 seconds.
Timer dict: {'Centroid normalization': 0.003, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 1
Assigning points to clusters took 0.03 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 1 took 1.05 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.03, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 2
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.008 seconds.
K-Means iteration 2 took 1.081 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.008, 'Check convergence': 0.001}
iteration 3
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 3 took 1.11 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 4
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 4 took 1.139 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 5
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 5 took 1.167 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 6
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 6 took 1.199 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 7
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 7 took 1.228 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 8
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 8 took 1.257 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 9
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 9 took 1.285 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 10
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 10 took 1.314 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 11
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 11 took 1.343 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 12
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 12 took 1.37 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 13
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.008 seconds.
K-Means iteration 13 took 1.402 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.008, 'Check convergence': 0.001}
iteration 14
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 14 took 1.43 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 15
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 15 took 1.458 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 16
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 16 took 1.486 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 17
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 17 took 1.515 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 18
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 18 took 1.543 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 19
Assigning points to clusters took 0.027 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 19 took 1.576 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.027, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 20
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.008 seconds.
K-Means iteration 20 took 1.608 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.008, 'Check convergence': 0.001}
iteration 21
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 21 took 1.637 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 22
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 22 took 1.665 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 23
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 23 took 1.693 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 24
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 24 took 1.721 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 25
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.006 seconds.
K-Means iteration 25 took 1.75 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.006, 'Check convergence': 0.001}
iteration 26
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 26 took 1.778 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 27
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 27 took 1.807 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 28
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 28 took 1.84 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 29
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 29 took 1.869 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 30
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 30 took 1.897 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 31
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 31 took 1.925 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 32
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 32 took 1.953 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 33
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 33 took 1.981 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 34
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 34 took 2.009 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 35
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.007 seconds.
K-Means iteration 35 took 2.04 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.007, 'Check convergence': 0.001}
iteration 36
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 36 took 2.069 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 37
Assigning points to clusters took 0.052 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 37 took 2.127 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.052, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 38
Assigning points to clusters took 0.042 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 38 took 2.186 seconds.
Timer dict: {'Centroid normalization': 0.011, 'Copy Centroids': 0.0, 'Assign clusters': 0.042, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 39
Assigning points to clusters took 0.027 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 39 took 2.219 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.027, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 40
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 40 took 2.252 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.027, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 41
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 41 took 2.281 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 42
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 42 took 2.31 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 43
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 43 took 2.338 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 44
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 44 took 2.366 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 45
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 45 took 2.395 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 46
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 46 took 2.423 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 47
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 47 took 2.452 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.006, 'Check convergence': 0.001}
iteration 48
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 48 took 2.481 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 49
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 49 took 2.509 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 50
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 50 took 2.537 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 51
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 51 took 2.566 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 52
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 52 took 2.594 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 53
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 53 took 2.622 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 54
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 54 took 2.65 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 55
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 55 took 2.68 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 56
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 56 took 2.708 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 57
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 57 took 2.736 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 58
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 58 took 2.764 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 59
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 59 took 2.792 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 60
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 60 took 2.821 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 61
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 61 took 2.849 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 62
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 62 took 2.878 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 63
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 63 took 2.906 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 64
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 64 took 2.934 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 65
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 65 took 2.963 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 66
Assigning points to clusters took 0.034 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 66 took 3.003 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.034, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 67
Assigning points to clusters took 0.039 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 67 took 3.049 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.039, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 68
Assigning points to clusters took 0.034 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 68 took 3.091 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.035, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 69
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 69 took 3.119 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 70
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 70 took 3.147 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 71
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 71 took 3.176 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 72
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 72 took 3.205 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 73
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 73 took 3.233 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 74
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 74 took 3.261 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 75
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 75 took 3.29 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.006, 'Check convergence': 0.001}
iteration 76
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 76 took 3.319 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 77
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 77 took 3.346 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 78
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 78 took 3.375 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 79
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 79 took 3.402 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 80
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 80 took 3.43 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 81
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 81 took 3.458 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 82
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 82 took 3.486 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 83
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 83 took 3.518 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 84
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 84 took 3.546 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 85
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 85 took 3.574 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 86
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 86 took 3.602 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 87
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 87 took 3.63 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 88
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 88 took 3.658 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 89
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 89 took 3.686 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 90
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 90 took 3.714 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 91
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 91 took 3.742 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 92
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 92 took 3.77 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 93
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 93 took 3.799 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 94
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 94 took 3.827 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 95
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 95 took 3.855 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 96
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 96 took 3.883 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 97
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 97 took 3.911 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 98
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 98 took 3.943 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 99
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 99 took 3.971 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
Took 388.604 seconds to cluster points.


Starting experiments for 4th seed
Running GPTExpansionClustering for seed 4
3080it [00:00, 4479353.79it/s]
load INSTRUCTOR_Transformer

max_seq_length  512
100%|█████████████████████████████████████████████████████████████████████████| 76/76 [00:00<00:00, 88.15it/s]
Total K-Means++ times: {'Initial Euclidean Distances': 0.010229790001176298, 'Pairwise Euclidean Distances': 0.7725585059961304, 'Compute candidate potentials': 0.0042052720236824825, 'Total K-Means++ time': 0.8743168660002993}
iteration 0
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 0 took 0.905 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 1
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 1 took 0.932 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 2
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 2 took 0.96 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 3
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 3 took 0.988 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 4
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 4 took 1.015 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 5
Assigning points to clusters took 0.03 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 5 took 1.051 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.03, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 6
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 6 took 1.081 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 7
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 7 took 1.109 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 8
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 8 took 1.136 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 9
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 9 took 1.163 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 10
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 10 took 1.19 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 11
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 11 took 1.218 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 12
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 12 took 1.246 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 13
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 13 took 1.273 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 14
Assigning points to clusters took 0.027 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 14 took 1.306 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.027, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 15
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 15 took 1.334 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 16
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 16 took 1.363 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 17
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 17 took 1.39 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 18
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 18 took 1.418 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 19
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 19 took 1.445 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 20
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 20 took 1.473 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 21
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 21 took 1.5 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 22
Assigning points to clusters took 0.033 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.011 seconds.
K-Means iteration 22 took 1.552 seconds.
Timer dict: {'Centroid normalization': 0.006, 'Copy Centroids': 0.0, 'Assign clusters': 0.034, 'Estimate cluster centers': 0.011, 'Check convergence': 0.001}
iteration 23
Assigning points to clusters took 0.047 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 23 took 1.606 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.047, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 24
Assigning points to clusters took 0.028 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 24 took 1.641 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.028, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 25
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 25 took 1.668 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 26
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 26 took 1.695 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 27
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 27 took 1.723 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 28
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 28 took 1.755 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 29
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 29 took 1.783 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 30
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 30 took 1.81 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 31
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 31 took 1.838 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 32
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 32 took 1.865 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 33
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 33 took 1.892 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 34
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 34 took 1.919 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 35
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 35 took 1.948 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 36
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 36 took 1.976 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 37
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 37 took 2.008 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 38
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 38 took 2.035 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 39
Assigning points to clusters took 0.047 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 39 took 2.089 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.047, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 40
Assigning points to clusters took 0.028 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 40 took 2.124 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.029, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 41
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 41 took 2.153 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 42
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 42 took 2.186 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 43
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 43 took 2.214 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 44
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 44 took 2.241 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 45
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 45 took 2.269 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 46
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 46 took 2.296 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 47
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 47 took 2.323 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 48
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 48 took 2.35 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 49
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 49 took 2.378 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 50
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 50 took 2.409 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 51
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 51 took 2.436 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 52
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 52 took 2.464 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 53
Assigning points to clusters took 0.029 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 53 took 2.499 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.029, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 54
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 54 took 2.527 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 55
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 55 took 2.554 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 56
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 56 took 2.581 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 57
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 57 took 2.61 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.006, 'Check convergence': 0.001}
iteration 58
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 58 took 2.638 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 59
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 59 took 2.665 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 60
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 60 took 2.694 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 61
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 61 took 2.722 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 62
Assigning points to clusters took 0.029 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 62 took 2.757 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.029, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 63
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 63 took 2.784 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 64
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 64 took 2.813 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.006, 'Check convergence': 0.001}
iteration 65
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 65 took 2.84 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 66
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 66 took 2.869 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 67
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 67 took 2.896 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 68
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 68 took 2.923 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 69
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 69 took 2.954 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 70
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 70 took 2.982 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 71
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 71 took 3.01 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 72
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 72 took 3.04 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 73
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 73 took 3.067 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 74
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 74 took 3.094 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 75
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 75 took 3.121 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 76
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 76 took 3.148 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 77
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 77 took 3.176 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 78
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 78 took 3.203 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 79
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 79 took 3.231 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 80
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 80 took 3.261 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 81
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 81 took 3.289 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 82
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 82 took 3.316 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 83
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 83 took 3.343 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 84
Assigning points to clusters took 0.057 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 84 took 3.406 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.057, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 85
Assigning points to clusters took 0.034 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 85 took 3.447 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.034, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 86
Assigning points to clusters took 0.046 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 86 took 3.499 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.046, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 87
Assigning points to clusters took 0.031 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 87 took 3.537 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.031, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 88
Assigning points to clusters took 0.042 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 88 took 3.586 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.043, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 89
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 89 took 3.613 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 90
Assigning points to clusters took 0.031 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 90 took 3.65 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.031, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 91
Assigning points to clusters took 0.039 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 91 took 3.696 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.039, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 92
Assigning points to clusters took 0.027 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 92 took 3.73 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.027, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 93
Assigning points to clusters took 0.027 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 93 took 3.764 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.028, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 94
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 94 took 3.791 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 95
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 95 took 3.818 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 96
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 96 took 3.845 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 97
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 97 took 3.873 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 98
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 98 took 3.901 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 99
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 99 took 3.929 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
Took 389.749 seconds to cluster points.


Starting experiments for 5th seed
Running GPTExpansionClustering for seed 5
3080it [00:00, 4404519.71it/s]
load INSTRUCTOR_Transformer

max_seq_length  512
100%|█████████████████████████████████████████████████████████████████████████| 76/76 [00:00<00:00, 79.83it/s]
Total K-Means++ times: {'Initial Euclidean Distances': 0.011415607004892081, 'Pairwise Euclidean Distances': 0.8414788240042981, 'Compute candidate potentials': 0.004416793992277235, 'Total K-Means++ time': 0.9673234069923637}
iteration 0
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 0 took 0.999 seconds.
Timer dict: {'Centroid normalization': 0.002, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 1
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 1 took 1.027 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 2
Assigning points to clusters took 0.035 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 2 took 1.068 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.035, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 3
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 3 took 1.096 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 4
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 4 took 1.124 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 5
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 5 took 1.151 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 6
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 6 took 1.182 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 7
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 7 took 1.21 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 8
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.007 seconds.
K-Means iteration 8 took 1.241 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.008, 'Check convergence': 0.001}
iteration 9
Assigning points to clusters took 0.03 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 9 took 1.277 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.03, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 10
Assigning points to clusters took 0.027 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 10 took 1.311 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.027, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 11
Assigning points to clusters took 0.033 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 11 took 1.35 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.033, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 12
Assigning points to clusters took 0.031 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 12 took 1.388 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.032, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 13
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 13 took 1.417 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 14
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 14 took 1.448 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 15
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 15 took 1.475 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 16
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 16 took 1.503 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 17
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 17 took 1.531 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 18
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 18 took 1.558 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 19
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.006 seconds.
K-Means iteration 19 took 1.587 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.007, 'Check convergence': 0.001}
iteration 20
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 20 took 1.616 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 21
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 21 took 1.644 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 22
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 22 took 1.672 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 23
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 23 took 1.699 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 24
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 24 took 1.726 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 25
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 25 took 1.754 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 26
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 26 took 1.785 seconds.
Timer dict: {'Centroid normalization': 0.004, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 27
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 27 took 1.816 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 28
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 28 took 1.843 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 29
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 29 took 1.871 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 30
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 30 took 1.898 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 31
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 31 took 1.926 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 32
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 32 took 1.953 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 33
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 33 took 1.98 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 34
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 34 took 2.008 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 35
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 35 took 2.038 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 36
Assigning points to clusters took 0.047 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 36 took 2.091 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.047, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 37
Assigning points to clusters took 0.032 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 37 took 2.129 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.032, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 38
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 38 took 2.161 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 39
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 39 took 2.189 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 40
Assigning points to clusters took 0.028 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 40 took 2.224 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.028, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 41
Assigning points to clusters took 0.032 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 41 took 2.262 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.032, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 42
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 42 took 2.289 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 43
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 43 took 2.316 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 44
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 44 took 2.344 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 45
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 45 took 2.372 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 46
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 46 took 2.399 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 47
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 47 took 2.426 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 48
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 48 took 2.453 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 49
Assigning points to clusters took 0.028 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 49 took 2.488 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.029, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 50
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 50 took 2.515 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 51
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 51 took 2.542 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 52
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 52 took 2.569 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 53
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 53 took 2.596 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 54
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 54 took 2.624 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 55
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 55 took 2.651 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 56
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 56 took 2.678 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 57
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 57 took 2.71 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 58
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 58 took 2.737 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 59
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 59 took 2.765 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 60
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 60 took 2.792 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 61
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 61 took 2.819 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 62
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 62 took 2.847 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 63
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 63 took 2.874 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 64
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 64 took 2.902 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 65
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 65 took 2.931 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 66
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 66 took 2.958 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 67
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 67 took 2.986 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 68
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 68 took 3.013 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 69
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 69 took 3.041 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 70
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 70 took 3.068 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 71
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 71 took 3.095 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 72
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 72 took 3.123 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 73
Assigning points to clusters took 0.028 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 73 took 3.157 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.028, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 74
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 74 took 3.185 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 75
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 75 took 3.212 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 76
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 76 took 3.241 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.006, 'Check convergence': 0.001}
iteration 77
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 77 took 3.269 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 78
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 78 took 3.296 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 79
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 79 took 3.323 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 80
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 80 took 3.35 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 81
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 81 took 3.38 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 82
Assigning points to clusters took 0.033 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 82 took 3.419 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.033, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 83
Assigning points to clusters took 0.039 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 83 took 3.465 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.039, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 84
Assigning points to clusters took 0.035 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 84 took 3.506 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.035, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 85
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 85 took 3.535 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 86
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 86 took 3.564 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 87
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 87 took 3.593 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 88
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 88 took 3.621 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 89
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 89 took 3.648 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 90
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 90 took 3.678 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 91
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 91 took 3.705 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 92
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 92 took 3.732 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 93
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 93 took 3.759 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 94
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 94 took 3.786 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 95
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 95 took 3.817 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 96
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 96 took 3.847 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 97
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 97 took 3.876 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 98
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 98 took 3.903 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 99
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 99 took 3.931 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
Took 388.737 seconds to cluster points.


Starting experiments for 6th seed
Running GPTExpansionClustering for seed 6
3080it [00:00, 4223097.85it/s]
load INSTRUCTOR_Transformer
max_seq_length  512
100%|████████████████████████████████████████████████████████████████| 76/76 [00:00<00:00, 86.26it/s]
Total K-Means++ times: {'Initial Euclidean Distances': 0.01019531799829565, 'Pairwise Euclidean Distances': 0.788992959947791, 'Compute candidate potentials': 0.0042006940057035536, 'Total K-Means++ time': 0.8945113549998496}
iteration 0
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 0 took 0.924 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 1
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 1 took 0.957 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 2
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 2 took 0.985 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 3
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 3 took 1.012 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 4
Assigning points to clusters took 0.03 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 4 took 1.048 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.03, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 5
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 5 took 1.075 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 6
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.006 seconds.
K-Means iteration 6 took 1.104 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.006, 'Check convergence': 0.001}
iteration 7
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 7 took 1.132 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 8
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 8 took 1.159 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 9
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 9 took 1.187 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 10
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 10 took 1.215 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 11
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 11 took 1.242 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 12
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 12 took 1.269 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 13
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 13 took 1.297 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 14
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 14 took 1.329 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 15
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 15 took 1.356 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 16
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 16 took 1.383 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 17
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 17 took 1.41 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 18
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 18 took 1.439 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 19
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 19 took 1.467 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 20
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 20 took 1.494 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 21
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 21 took 1.522 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 22
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 22 took 1.552 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 23
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 23 took 1.579 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 24
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 24 took 1.606 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 25
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 25 took 1.633 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 26
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 26 took 1.66 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 27
Assigning points to clusters took 0.029 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 27 took 1.696 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.029, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 28
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 28 took 1.728 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 29
Assigning points to clusters took 0.039 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 29 took 1.774 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.039, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 30
Assigning points to clusters took 0.03 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 30 took 1.811 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.03, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 31
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 31 took 1.838 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 32
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 32 took 1.865 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 33
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 33 took 1.893 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 34
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 34 took 1.92 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 35
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 35 took 1.947 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 36
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 36 took 1.976 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 37
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 37 took 2.004 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 38
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 38 took 2.031 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 39
Assigning points to clusters took 0.061 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 39 took 2.098 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.061, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 40
Assigning points to clusters took 0.029 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 40 took 2.134 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.029, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 41
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 41 took 2.161 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 42
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 42 took 2.192 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 43
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 43 took 2.219 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 44
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 44 took 2.247 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 45
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 45 took 2.274 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 46
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 46 took 2.302 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.002}
iteration 47
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 47 took 2.33 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 48
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 48 took 2.357 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 49
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 49 took 2.386 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 50
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 50 took 2.415 seconds.
Timer dict: {'Centroid normalization': 0.003, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 51
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 51 took 2.444 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 52
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 52 took 2.471 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 53
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 53 took 2.498 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 54
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 54 took 2.526 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 55
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 55 took 2.553 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 56
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 56 took 2.581 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 57
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 57 took 2.608 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 58
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 58 took 2.638 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 59
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 59 took 2.665 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 60
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 60 took 2.693 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 61
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 61 took 2.72 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 62
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 62 took 2.747 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 63
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 63 took 2.774 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 64
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 64 took 2.802 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 65
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 65 took 2.829 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 66
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 66 took 2.859 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 67
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 67 took 2.886 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 68
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 68 took 2.913 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 69
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 69 took 2.941 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 70
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 70 took 2.968 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 71
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 71 took 2.996 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 72
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 72 took 3.023 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 73
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 73 took 3.05 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 74
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 74 took 3.081 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 75
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 75 took 3.109 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 76
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 76 took 3.136 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 77
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 77 took 3.163 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 78
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 78 took 3.191 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 79
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 79 took 3.219 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 80
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 80 took 3.246 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 81
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.006 seconds.
K-Means iteration 81 took 3.279 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.006, 'Check convergence': 0.001}
iteration 82
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 82 took 3.31 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 83
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 83 took 3.337 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 84
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 84 took 3.366 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 85
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 85 took 3.394 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 86
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 86 took 3.421 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 87
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 87 took 3.451 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 88
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 88 took 3.48 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.003}
iteration 89
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 89 took 3.508 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 90
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 90 took 3.535 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 91
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 91 took 3.562 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 92
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 92 took 3.59 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 93
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 93 took 3.618 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 94
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 94 took 3.645 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 95
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 95 took 3.672 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 96
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 96 took 3.701 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 97
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 97 took 3.729 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 98
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 98 took 3.756 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 99
Assigning points to clusters took 0.03 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 99 took 3.792 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.03, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
Took 397.126 seconds to cluster points.


Starting experiments for 7th seed
Running GPTExpansionClustering for seed 7
3080it [00:00, 4214830.77it/s]
load INSTRUCTOR_Transformer

max_seq_length  512
100%|█████████████████████████████████████████████████████████████████████████| 76/76 [00:01<00:00, 73.43it/s]
Total K-Means++ times: {'Initial Euclidean Distances': 0.011382343000150286, 'Pairwise Euclidean Distances': 0.9365939949202584, 'Compute candidate potentials': 0.004439349970198236, 'Total K-Means++ time': 1.0492934030044125}
iteration 0
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 0 took 1.082 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 1
Assigning points to clusters took 0.048 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.011 seconds.
K-Means iteration 1 took 1.143 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.048, 'Estimate cluster centers': 0.011, 'Check convergence': 0.001}
iteration 2
Assigning points to clusters took 0.043 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 2 took 1.193 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.043, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 3
Assigning points to clusters took 0.047 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 3 took 1.246 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.047, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 4
Assigning points to clusters took 0.046 seconds.
Handling empty clusters took 0.001 seconds.
Computing cluster centers took 0.007 seconds.
K-Means iteration 4 took 1.301 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.047, 'Estimate cluster centers': 0.007, 'Check convergence': 0.001}
iteration 5
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 5 took 1.331 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 6
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 6 took 1.362 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 7
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 7 took 1.393 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 8
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 8 took 1.424 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 9
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 9 took 1.454 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 10
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 10 took 1.484 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 11
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 11 took 1.517 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 12
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 12 took 1.547 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 13
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 13 took 1.578 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 14
Assigning points to clusters took 0.034 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 14 took 1.618 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.034, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 15
Assigning points to clusters took 0.038 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 15 took 1.662 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.038, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 16
Assigning points to clusters took 0.033 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 16 took 1.702 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.034, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 17
Assigning points to clusters took 0.041 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 17 took 1.75 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.042, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 18
Assigning points to clusters took 0.031 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 18 took 1.788 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.032, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 19
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 19 took 1.817 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 20
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 20 took 1.847 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 21
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 21 took 1.878 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 22
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 22 took 1.907 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 23
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 23 took 1.938 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 24
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 24 took 1.971 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.027, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 25
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 25 took 2.003 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 26
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 26 took 2.033 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 27
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 27 took 2.06 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 28
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 28 took 2.087 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 29
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 29 took 2.114 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 30
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 30 took 2.141 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 31
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.007 seconds.
K-Means iteration 31 took 2.171 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.007, 'Check convergence': 0.001}
iteration 32
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 32 took 2.198 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 33
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 33 took 2.225 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 34
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 34 took 2.251 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 35
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 35 took 2.279 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 36
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 36 took 2.306 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 37
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 37 took 2.333 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 38
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 38 took 2.36 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 39
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 39 took 2.392 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 40
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 40 took 2.419 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 41
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 41 took 2.446 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 42
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 42 took 2.473 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 43
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 43 took 2.5 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 44
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 44 took 2.527 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 45
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 45 took 2.554 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 46
Assigning points to clusters took 0.027 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 46 took 2.589 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.027, 'Estimate cluster centers': 0.005, 'Check convergence': 0.003}
iteration 47
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 47 took 2.617 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 48
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 48 took 2.645 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 49
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 49 took 2.672 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 50
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 50 took 2.699 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 51
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 51 took 2.727 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 52
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 52 took 2.755 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 53
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 53 took 2.784 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 54
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 54 took 2.814 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 55
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 55 took 2.842 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 56
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 56 took 2.868 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 57
Assigning points to clusters took 0.031 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 57 took 2.906 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.031, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 58
Assigning points to clusters took 0.035 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 58 took 2.948 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.036, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 59
Assigning points to clusters took 0.064 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 59 took 3.019 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.064, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 60
Assigning points to clusters took 0.039 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 60 took 3.064 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.039, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 61
Assigning points to clusters took 0.033 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 61 took 3.103 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.033, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 62
Assigning points to clusters took 0.028 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 62 took 3.138 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.029, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 63
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 63 took 3.165 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 64
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 64 took 3.192 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 65
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 65 took 3.222 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 66
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 66 took 3.249 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 67
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 67 took 3.275 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 68
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 68 took 3.302 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 69
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 69 took 3.331 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 70
Assigning points to clusters took 0.046 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 70 took 3.384 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.047, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 71
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 71 took 3.411 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 72
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 72 took 3.443 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 73
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 73 took 3.47 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 74
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 74 took 3.497 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 75
Assigning points to clusters took 0.029 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 75 took 3.533 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.029, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 76
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 76 took 3.56 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 77
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 77 took 3.587 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 78
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 78 took 3.616 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 79
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 79 took 3.648 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 80
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 80 took 3.675 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 81
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 81 took 3.702 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 82
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 82 took 3.729 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 83
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 83 took 3.756 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 84
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 84 took 3.782 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 85
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 85 took 3.809 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 86
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 86 took 3.836 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 87
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 87 took 3.866 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 88
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 88 took 3.893 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 89
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 89 took 3.92 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 90
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 90 took 3.947 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 91
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 91 took 3.973 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 92
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 92 took 4.001 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 93
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 93 took 4.028 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 94
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 94 took 4.054 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 95
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 95 took 4.085 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 96
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 96 took 4.112 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 97
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 97 took 4.139 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 98
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 98 took 4.166 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 99
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 99 took 4.193 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
Took 389.178 seconds to cluster points.


Starting experiments for 8th seed
Running GPTExpansionClustering for seed 8
3080it [00:00, 4404519.71it/s]
load INSTRUCTOR_Transformer

max_seq_length  512
100%|█████████████████████████████████████████████████████████████████████████| 76/76 [00:00<00:00, 83.81it/s]
Total K-Means++ times: {'Initial Euclidean Distances': 0.009044546997756697, 'Pairwise Euclidean Distances': 0.8175114659679821, 'Compute candidate potentials': 0.0042781539232237265, 'Total K-Means++ time': 0.9177986669965321}
iteration 0
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 0 took 0.947 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 1
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 1 took 0.975 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 2
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.007 seconds.
K-Means iteration 2 took 1.004 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.007, 'Check convergence': 0.001}
iteration 3
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 3 took 1.031 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 4
Assigning points to clusters took 0.028 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 4 took 1.065 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.028, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 5
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 5 took 1.093 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 6
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 6 took 1.12 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 7
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 7 took 1.149 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 8
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 8 took 1.176 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 9
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 9 took 1.203 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 10
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 10 took 1.23 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 11
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 11 took 1.257 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 12
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 12 took 1.284 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 13
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 13 took 1.311 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 14
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 14 took 1.338 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 15
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 15 took 1.369 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 16
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 16 took 1.396 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 17
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 17 took 1.423 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 18
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 18 took 1.45 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 19
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 19 took 1.477 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 20
Assigning points to clusters took 0.026 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 20 took 1.509 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 21
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 21 took 1.536 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 22
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 22 took 1.563 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 23
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 23 took 1.593 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 24
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 24 took 1.62 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 25
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 25 took 1.647 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 26
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 26 took 1.674 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 27
Assigning points to clusters took 0.031 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 27 took 1.712 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.032, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 28
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 28 took 1.739 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 29
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 29 took 1.767 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 30
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 30 took 1.797 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 31
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 31 took 1.824 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 32
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 32 took 1.852 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 33
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 33 took 1.879 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 34
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 34 took 1.906 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 35
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 35 took 1.933 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 36
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 36 took 1.962 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 37
Assigning points to clusters took 0.044 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 37 took 2.013 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.045, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 38
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 38 took 2.041 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 39
Assigning points to clusters took 0.056 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 39 took 2.103 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.056, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 40
Assigning points to clusters took 0.031 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 40 took 2.141 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.031, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 41
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 41 took 2.172 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 42
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 42 took 2.199 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 43
Assigning points to clusters took 0.029 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 43 took 2.235 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.03, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 44
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 44 took 2.263 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 45
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 45 took 2.29 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 46
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 46 took 2.317 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 47
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 47 took 2.344 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 48
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 48 took 2.373 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 49
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 49 took 2.4 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 50
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 50 took 2.427 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 51
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 51 took 2.458 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 52
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 52 took 2.485 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 53
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 53 took 2.512 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 54
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 54 took 2.539 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 55
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 55 took 2.57 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 56
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 56 took 2.598 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 57
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 57 took 2.625 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 58
Assigning points to clusters took 0.037 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 58 took 2.668 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.037, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 59
Assigning points to clusters took 0.03 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 59 took 2.704 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.03, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 60
Assigning points to clusters took 0.036 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.011 seconds.
K-Means iteration 60 took 2.753 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.036, 'Estimate cluster centers': 0.011, 'Check convergence': 0.001}
iteration 61
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 61 took 2.78 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 62
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 62 took 2.807 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 63
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 63 took 2.835 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 64
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 64 took 2.861 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 65
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 65 took 2.892 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 66
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 66 took 2.919 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 67
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 67 took 2.946 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 68
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 68 took 2.974 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 69
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 69 took 3.001 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 70
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 70 took 3.028 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 71
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 71 took 3.055 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 72
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 72 took 3.082 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 73
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 73 took 3.113 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 74
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 74 took 3.14 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 75
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 75 took 3.167 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 76
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 76 took 3.194 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 77
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 77 took 3.221 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 78
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 78 took 3.248 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 79
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 79 took 3.275 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 80
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 80 took 3.302 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 81
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 81 took 3.333 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 82
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 82 took 3.36 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 83
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 83 took 3.387 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 84
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 84 took 3.414 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 85
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 85 took 3.441 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 86
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 86 took 3.468 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 87
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 87 took 3.495 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 88
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 88 took 3.522 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 89
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 89 took 3.553 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 90
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 90 took 3.58 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.02, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 91
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 91 took 3.606 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 92
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 92 took 3.633 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 93
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 93 took 3.66 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 94
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 94 took 3.687 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 95
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 95 took 3.714 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 96
Assigning points to clusters took 0.02 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 96 took 3.741 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 97
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 97 took 3.773 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 98
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 98 took 3.801 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 99
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 99 took 3.828 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
Took 379.733 seconds to cluster points.


Starting experiments for 9th seed
Running GPTExpansionClustering for seed 9
3080it [00:00, 2558616.82it/s]
load INSTRUCTOR_Transformer

max_seq_length  512
100%|█████████████████████████████████████████████████████████████████████████| 76/76 [00:00<00:00, 81.88it/s]
Total K-Means++ times: {'Initial Euclidean Distances': 0.010304026000085287, 'Pairwise Euclidean Distances': 0.837303560008877, 'Compute candidate potentials': 0.004337775069870986, 'Total K-Means++ time': 0.9403680519899353}
iteration 0
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 0 took 0.97 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 1
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 1 took 1.002 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 2
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 2 took 1.029 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 3
Assigning points to clusters took 0.031 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 3 took 1.066 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.031, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 4
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 4 took 1.093 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 5
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 5 took 1.12 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 6
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 6 took 1.148 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 7
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 7 took 1.176 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 8
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 8 took 1.203 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 9
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 9 took 1.23 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 10
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 10 took 1.258 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 11
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 11 took 1.285 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 12
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 12 took 1.312 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 13
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 13 took 1.339 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 14
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 14 took 1.371 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.026, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 15
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 15 took 1.398 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 16
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 16 took 1.425 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 17
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 17 took 1.455 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 18
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 18 took 1.482 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 19
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 19 took 1.51 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 20
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 20 took 1.538 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 21
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 21 took 1.565 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 22
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 22 took 1.594 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 23
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 23 took 1.621 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 24
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 24 took 1.649 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 25
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 25 took 1.677 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 26
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 26 took 1.704 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 27
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 27 took 1.731 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 28
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 28 took 1.758 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 29
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 29 took 1.786 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 30
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 30 took 1.816 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 31
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 31 took 1.844 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 32
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 32 took 1.871 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 33
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 33 took 1.899 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 34
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 34 took 1.926 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 35
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 35 took 1.953 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 36
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 36 took 1.981 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 37
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 37 took 2.008 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 38
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 38 took 2.037 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 39
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 39 took 2.065 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 40
Assigning points to clusters took 0.049 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 40 took 2.12 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.049, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 41
Assigning points to clusters took 0.05 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 41 took 2.177 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.05, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 42
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 42 took 2.204 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 43
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 43 took 2.231 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 44
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 44 took 2.263 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 45
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 45 took 2.29 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 46
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 46 took 2.317 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 47
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 47 took 2.346 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 48
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 48 took 2.373 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 49
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 49 took 2.4 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 50
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 50 took 2.427 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 51
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 51 took 2.455 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 52
Assigning points to clusters took 0.023 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 52 took 2.485 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.023, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 53
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 53 took 2.512 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 54
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 54 took 2.539 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 55
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 55 took 2.567 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 56
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 56 took 2.594 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 57
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 57 took 2.621 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 58
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 58 took 2.648 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 59
Assigning points to clusters took 0.027 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 59 took 2.682 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.027, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 60
Assigning points to clusters took 0.031 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 60 took 2.72 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.031, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 61
Assigning points to clusters took 0.037 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 61 took 2.763 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.037, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 62
Assigning points to clusters took 0.032 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 62 took 2.801 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.032, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 63
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 63 took 2.829 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 64
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 64 took 2.856 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 65
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 65 took 2.886 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 66
Assigning points to clusters took 0.048 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 66 took 2.94 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.048, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 67
Assigning points to clusters took 0.041 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 67 took 2.988 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.041, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 68
Assigning points to clusters took 0.032 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 68 took 3.027 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.032, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 69
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 69 took 3.054 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 70
Assigning points to clusters took 0.06 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 70 took 3.121 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.06, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 71
Assigning points to clusters took 0.047 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 71 took 3.173 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.047, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 72
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 72 took 3.201 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 73
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 73 took 3.228 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 74
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 74 took 3.255 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 75
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 75 took 3.282 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 76
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 76 took 3.31 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 77
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 77 took 3.34 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 78
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 78 took 3.367 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 79
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 79 took 3.394 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 80
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 80 took 3.421 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 81
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 81 took 3.449 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 82
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 82 took 3.476 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 83
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 83 took 3.503 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 84
Assigning points to clusters took 0.022 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 84 took 3.531 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.022, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 85
Assigning points to clusters took 0.025 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 85 took 3.562 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.025, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 86
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 86 took 3.59 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 87
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 87 took 3.617 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 88
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 88 took 3.644 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 89
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 89 took 3.671 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 90
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 90 took 3.698 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 91
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 91 took 3.726 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 92
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 92 took 3.753 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 93
Assigning points to clusters took 0.024 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.005 seconds.
K-Means iteration 93 took 3.783 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.024, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 94
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 94 took 3.81 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 95
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 95 took 3.838 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 96
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 96 took 3.865 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 97
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 97 took 3.892 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
iteration 98
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 98 took 3.919 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.004, 'Check convergence': 0.001}
iteration 99
Assigning points to clusters took 0.021 seconds.
Handling empty clusters took 0.0 seconds.
Computing cluster centers took 0.004 seconds.
K-Means iteration 99 took 3.946 seconds.
Timer dict: {'Centroid normalization': 0.001, 'Copy Centroids': 0.0, 'Assign clusters': 0.021, 'Estimate cluster centers': 0.005, 'Check convergence': 0.001}
Took 375.389 seconds to cluster points.


{
  "GPTExpansionClustering": {
    "rand": {
      "mean": 0.5811966889404675,
      "std": 0.0
    },
    "nmi": {
      "mean": 0.8327835537186827,
      "std": 0.0
    },
    "acc": {
      "mean": 0.677922077922078,
      "std": 1.1102230246251565e-16
    },
    "general_pairwise_f1": {
      "mean": 0.587010836845274,
      "std": 1.1102230246251565e-16
    }
  }
}
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print("hello")
hello
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